Groups of graphs of groups

We classify all groups of color preserving automorphisms (isometries) of edge colored complete graphs derived from finite groups

Barrier Formation in the Human Fetus is Patterned

We recently demonstrated patterned stratum corneum maturation and skin barrier formation during fetal development in rodents and rabbit. The presence of skin patterning in these mammals led us to predict patterned barrier formation during human infant development. Here we extend our mammalian study and demonstrate patterned stratum corneum development and skin barrier formation in the pre-term human infant. Surprisingly, we show initiation of human barrier regionally as early as 20–24 wk gestational age (22–26 wk menstrual age), bringing barrier formation close to the time of periderm disaggregation. We use the mouse model to show that patterns of periderm disaggregation mirrors barrier formation. Periderm disaggregation follows and recapitulates barrier pattern, suggesting a relationship between the processes. This work reveals regional patterning in skin maturation and barrier formation in the human infant and demonstrates that initiation of human skin barrier formation in utero coincides with the current lower limit of viability of the pre-term infant

Brief sensory deprivation triggers plasticity of dopamine-synthesising enzyme expression in genetically labelled olfactory bulb dopaminergic neurons

In the glomerular layer of the olfactory bulb, local dopaminergic interneurons play a key role in regulating the flow of sensory information from nose to cortex. These dual dopamine- and GABA-releasing cells are capable of marked experience-dependent changes in the expression of neurotransmitter-synthesising enzymes, including tyrosine hydroxylase (TH). However, such plasticity has most commonly been studied in cell populations identified by their expression of the enzyme being studied, and after long periods of sensory deprivation. Here, instead, we used brief 1- or 3-day manipulations of olfactory experience in juvenile mice, coupled with a conditional genetic approach that labelled neurons contingent upon their expression of the dopamine transporter (DAT-tdTomato). This enabled us to evaluate the potential for rapid changes in neurotransmitter-synthesising enzyme expression in an independently identified neuronal population. Our labelling strategy showed good specificity for olfactory bulb dopaminergic neurons, whilst revealing a minority sub-population of non-dopaminergic DAT-tdTomato cells that expressed the calcium-binding protein calretinin. Crucially, the proportions of these neuronal subtypes were not affected by brief alterations in sensory experience. Short-term olfactory manipulations also produced no significant changes in immunofluorescence or whole-bulb mRNA for the GABA-synthesising enzyme GAD67/Gad1. However, in bulbar DAT-tdTomato neurons brief sensory deprivation was accompanied by a transient, small drop in immunofluorescence for the dopamine-synthesising enzyme dopa decarboxylase (DDC), and a sustained decrease for TH. Deprivation also produced a sustained decrease in whole-bulb Th mRNA. Careful characterisation of an independently identified, genetically labelled neuronal population therefore enabled us to uncover rapid experience-dependent changes in dopamine-synthesising enzyme expression

Ultra-Filtration of Human Serum for Improved Quantitative Analysis of Low Molecular Weight Biomarkers using ATR-IR Spectroscopy

Infrared spectroscopy is a reliable, rapid and cost effective characterisation technique, delivering a molecular finger print of the sample. It is expected that its sensitivity would enable detection of small chemical variations in biological samples associated with disease. ATR-IR is particularly suitable for liquid sample analysis and, although air drying is commonly performed before data collection, just a drop of human serum is enough for screening and early diagnosis. However, the dynamic range of constituent biochemical concentrations in the serum composition remains a limiting factor to the reliability of the technique. Using glucose as a model spike in human serum, it has been demonstrated in the present study that fractionating the serum prior to spectroscopic analysis can considerably improve the precision and accuracy of quantitative models based on the Partial Least Squares Regression algorithm. By depleting the abundant high molecular weight proteins, which otherwise dominate the spectral signatures collected, the ability to monitor changes in the concentrations of the low molecular weight constituents is enhanced. The Root Mean Square Error for the Validation set (RMSEV) has been improved by a factor of 5 following human serum processing with an average relative error in the predictive values below 1% is achieved. Moreover, the approach is easily transferable to different bodily fluids, which would support the development of more efficient and suitable clinical protocols for exploration of vibrational spectroscopy based ex-vivo diagnostic tools

A global analysis of genetic interactions in Caenorhabditis elegans

Abstract Background Understanding gene function and genetic relationships is fundamental to our efforts to better understand biological systems. Previous studies systematically describing genetic interactions on a global scale have either focused on core biological processes in protozoans or surveyed catastrophic interactions in metazoans. Here, we describe a reliable high-throughput approach capable of revealing both weak and strong genetic interactions in the nematode Caenorhabditis elegans. Results We investigated interactions between 11 'query' mutants in conserved signal transduction pathways and hundreds of 'target' genes compromised by RNA interference (RNAi). Mutant-RNAi combinations that grew more slowly than controls were identified, and genetic interactions inferred through an unbiased global analysis of the interaction matrix. A network of 1,246 interactions was uncovered, establishing the largest metazoan genetic-interaction network to date. We refer to this approach as systematic genetic interaction analysis (SGI). To investigate how genetic interactions connect genes on a global scale, we superimposed the SGI network on existing networks of physical, genetic, phenotypic and coexpression interactions. We identified 56 putative functional modules within the superimposed network, one of which regulates fat accumulation and is coordinated by interactions with bar-1(ga80), which encodes a homolog of β-catenin. We also discovered that SGI interactions link distinct subnetworks on a global scale. Finally, we showed that the properties of genetic networks are conserved between C. elegans and Saccharomyces cerevisiae, but that the connectivity of interactions within the current networks is not. Conclusions Synthetic genetic interactions may reveal redundancy among functional modules on a global scale, which is a previously unappreciated level of organization within metazoan systems. Although the buffering between functional modules may differ between species, studying these differences may provide insight into the evolution of divergent form and function

Analysis of Bodily Fluids Using Vibrational Spectroscopy: a Direct Comparison of Raman Scattering and Infrared Absorption Techniques for the Case of Glucose in Blood Serum

Analysis of biomarkers present in the blood stream can potentially deliver crucial information on patient health and indicate the presence of numerous pathologies. The potential of vibrational spectroscopic analysis of human serum for diagnostic purposes has been widely investigated and, in recent times, infrared absorption spectroscopy, coupled with ultra-filtration and multivariate analysis techniques, has attracted increasing attention, both clinical and commercial. However, such methods commonly employ a drying step, which may hinder the clinical work flow and thus hamper their clinical deployment. As an alternative, this study explores the use of Raman spectroscopy, similarly coupled with ultra-filtration and multivariate analysis techniques, to quantitatively monitor diagnostically relevant changes of glucose in liquid serum samples, and compares the results with similar analysis protocols using infrared spectroscopy of dried samples. The analysis protocols to detect the imbalances in glucose using Raman spectroscopy are first demonstrated for aqueous solutions and spiked serum samples. As in the case of infrared absorption studies, centrifugal filtration is utilised to deplete abundant analytes and to reveal the spectral features of Low Molecular Weight Fraction analytes in order to improve spectral sensitivity and detection limits. Improved Root Mean Square Error of Cross Validation (RMSECV) was observed for Raman prediction models, whereas slightly higher R2 values were reported for infrared absorption prediction models. Summarising, it is demonstrated that the Raman analysis protocol can yield accuracies which are comparable with those reported using infrared absorption based measurements of dried serum, without the need for additional drying steps

How do spatially distinct frequency specific MEG networks emerge from one underlying structural connectome? The role of the structural eigenmodes

Functional networks obtained from magnetoencephalography (MEG) from different frequency bands show distinct spatial patterns. It remains to be elucidated how distinct spatial patterns in MEG networks emerge given a single underlying structural network. Recent work has suggested that the eigenmodes of the structural network might serve as a basis set for functional network patterns in the case of functional MRI. Here, we take this notion further in the context of frequency band specific MEG networks. We show that a selected set of eigenmodes of the structural network can predict different frequency band specific networks in the resting state, ranging from delta (1–4 Hz) to the high gamma band (40–70 Hz). These predictions outperform predictions based from surrogate data, suggesting a genuine relationship between eigenmodes of the structural network and frequency specific MEG networks. We then show that the relevant set of eigenmodes can be excited in a network of neural mass models using linear stability analysis only by including delays. Excitation of an eigenmode in this context refers to a dynamic instability of a network steady state to a spatial pattern with a corresponding coherent temporal oscillation. Simulations verify the results from linear stability analysis and suggest that theta, alpha and beta band networks emerge very near to the bifurcation. The delta and gamma bands in the resting state emerges further away from the bifurcation. These results show for the first time how delayed interactions can excite the relevant set of eigenmodes that give rise to frequency specific functional connectivity patterns

A 6,000-year record of environmental change from the eastern Pacific margin of central Mexico

The transition from the mid- to late-Holocene in MesoAmerica saw increasing complexity in spatial patterns of change. Records from the western part of the region are sparse, with lacustrine sequences affected by long term anthropogenic disturbance or lacking chronological resolution. Here, we present a continuous palaeoecological and geochemical record from Laguna de Juanacatlán, a remote lake in the mountains of the western TMVB. Diatom assemblages, XRF scanning data and bulk organic geochemistry from a well-dated, 7.25-m laminated sequence were combined with summary pollen data from a 9-m partially laminated core to provide a continuous record of catchment and lake ecosystem changes over the last c. 6,000 years. Relatively humid conditions prevailed prior to c. 5.1 cal ka, which supported dense oak-pine forest cover around a deep, stratified lake. A trend towards drier conditions began c. 5.1 cal ka, intensifying after 4.0 cal ka, consistent with weakening of the North American Monsoon. Between 3.0 and 1.2 cal ka, lower lake levels and variable catchment run-off are consistent with increasing ENSO influence observed in the Late Holocene in the neotropics. From 1.2 to 0.9 cal ka, a marked change to catchment stability and more intense stratification reflected drier conditions and / or reduced rainfall variability and possibly warmer temperatures. After 0.9 cal ka, conditions were wetter, with an increase in catchment disturbance associated with the combined effects of climate and human activity. In recent decades, the lake ecosystem has changed markedly, possibly in response to recent climate change as well as local catchment dynamics

Gene expression by marrow stromal cells in a porous collagen-glycosaminoglycan scaffold is affected by pore size and mechanical stimulation.

Marrow stromal cell (MSC) populations, which are a potential source of undifferentiated mesenchymal cells, and culture scaffolds that mimic natural extracellular matrix are attractive options for orthopaedic tissue engineering. A type I collagen-glycosaminoglycan (CG) scaffold that has previously been used clinically for skin regeneration was recently shown to support expression of bone-associated proteins and mineralisation by MSCs cultured in the presence of osteogenic supplements. Here we follow RNA markers of osteogenic differentiation in this scaffold. We demonstrate that transcripts of the late stage markers bone sialoprotein and osteocalcin are present at higher levels in scaffold constructs than in two-dimensional culture, and that considerable gene induction can occur in this scaffold even in the absence of soluble osteogenic supplements. We also find that bone-related gene expression is affected by pore size, mechanical constraint, and uniaxial cyclic strain of the CG scaffold. The data presented here further establish the CG scaffold as a potentially valuable substrate for orthopaedic tissue engineering and for research on the mechanical interactions between cells and their environment, and suggest that a more freely-contracting scaffold with larger pore size may provide an environment more conducive to osteogenesis than constrained scaffolds with smaller pore sizes