Identification and Characterisation of the Early Differentiating Cells in Neural Differentiation of Human Embryonic Stem Cells

One of the challenges in studying early differentiation of human embryonic stem cells (hESCs) is being able to discriminate the initial differentiated cells from the original pluripotent stem cells and their committed progenies. It remains unclear how a pluripotent stem cell becomes a lineage-specific cell type during early development, and how, or if, pluripotent genes, such as Oct4 and Sox2, play a role in this transition. Here, by studying the dynamic changes in the expression of embryonic surface antigens, we identified the sequential loss of Tra-1-81 and SSEA4 during hESC neural differentiation and isolated a transient Tra-1-81(−)/SSEA4(+) (TR−/S4+) cell population in the early stage of neural differentiation. These cells are distinct from both undifferentiated hESCs and their committed neural progenitor cells (NPCs) in their gene expression profiles and response to extracellular signalling; they co-express both the pluripotent gene Oct4 and the neural marker Pax6. Furthermore, these TR−/S4+ cells are able to produce cells of both neural and non-neural lineages, depending on their environmental cues. Our results demonstrate that expression of the pluripotent factor Oct4 is progressively downregulated and is accompanied by the gradual upregulation of neural genes, whereas the pluripotent factor Sox2 is consistently expressed at high levels, indicating that these pluripotent factors may play different roles in the regulation of neural differentiation. The identification of TR-S4+ cells provides a cell model for further elucidation of the molecular mechanisms underlying hESC neural differentiation

Hydrogen adsorption capacity of adatoms on double carbon vacancies of graphene: A trend study from first principles

Structural stability and hydrogen adsorption capacity are two key quantities in evaluating the potential of metal-adatom decorated graphene for hydrogen storage and related devices. We have carried out extensive density functional theory calculations for the adsorption of hydrogen molecules on 12 different adatom (Ag, Au, Ca, Li, Mg, Pd, Pt, Sc, Sr, Ti, Y, and Zr) decorated graphene surfaces where the adatoms are found to be stabilized on double carbon vacancies, thus overcoming the "clustering problem" that occurs for adatoms on pristine graphene. Ca and Sr are predicted to bind the greatest number, namely six, of H2 molecules. We find an interesting correlation between the hydrogen capacity and the change of charge distribution with increasing H2 adsorption, where Ca, Li, Mg, Sc, Ti, Y, Sr, and Zr adatoms are partial electron donors and Ag, Au, Pd, and Pt are partial electron acceptors. The "18-electron rule" for predicting maximum hydrogen capacity is found not to be a reliable indicator for these systems. © 2013 American Physical Society

Paternal obesity is associated with IGF2 hypomethylation in newborns: results from a Newborn Epigenetics Study (NEST) cohort

Data from epidemiological and animal model studies suggest that nutrition during pregnancy may affect the health status of subsequent generations. These transgenerational effects are now being explained by disruptions at the level of the epigenetic machinery. Besides in vitro environmental exposures, the possible impact on the reprogramming of methylation profiles at imprinted genes at a much earlier time point, such as during spermatogenesis or oogenesis, has not previously been considered. In this study, our aim was to determine associations between preconceptional obesity and DNA methylation profiles in the offspring, particularly at the differentially methylated regions (DMRs) of the imprinted Insulin-like Growth Factor 2 (IGF2) gene

Bundled Crossings Revisited

An effective way to reduce clutter in a graph drawing that has (many) crossings is to group edges that travel in parallel into \emph{bundles}. Each edge can participate in many such bundles. Any crossing in this bundled graph occurs between two bundles, i.e., as a \emph{bundled crossing}. We consider the problem of bundled crossing minimization: A graph is given and the goal is to find a bundled drawing with at most $k$ bundled crossings. We show that the problem is NP-hard when we require a simple drawing. Our main result is an FPT algorithm (in $k$) when we require a simple circular layout. These results make use of the connection between bundled crossings and graph genus.Comment: Appears in the Proceedings of the 27th International Symposium on Graph Drawing and Network Visualization (GD 2019

Patterns of subnet usage reveal distinct scales of regulation in the transcriptional regulatory network of Escherichia coli

The set of regulatory interactions between genes, mediated by transcription factors, forms a species' transcriptional regulatory network (TRN). By comparing this network with measured gene expression data one can identify functional properties of the TRN and gain general insight into transcriptional control. We define the subnet of a node as the subgraph consisting of all nodes topologically downstream of the node, including itself. Using a large set of microarray expression data of the bacterium Escherichia coli, we find that the gene expression in different subnets exhibits a structured pattern in response to environmental changes and genotypic mutation. Subnets with less changes in their expression pattern have a higher fraction of feed-forward loop motifs and a lower fraction of small RNA targets within them. Our study implies that the TRN consists of several scales of regulatory organization: 1) subnets with more varying gene expression controlled by both transcription factors and post-transcriptional RNA regulation, and 2) subnets with less varying gene expression having more feed-forward loops and less post-transcriptional RNA regulation.Comment: 14 pages, 8 figures, to be published in PLoS Computational Biolog

CARDIAN: a novel computational approach for real-time end-diastolic frame detection in intravascular ultrasound using bidirectional attention networks

INTRODUCTION: Changes in coronary artery luminal dimensions during the cardiac cycle can impact the accurate quantification of volumetric analyses in intravascular ultrasound (IVUS) image studies. Accurate ED-frame detection is pivotal for guiding interventional decisions, optimizing therapeutic interventions, and ensuring standardized volumetric analysis in research studies. Images acquired at different phases of the cardiac cycle may also lead to inaccurate quantification of atheroma volume due to the longitudinal motion of the catheter in relation to the vessel. As IVUS images are acquired throughout the cardiac cycle, end-diastolic frames are typically identified retrospectively by human analysts to minimize motion artefacts and enable more accurate and reproducible volumetric analysis. METHODS: In this paper, a novel neural network-based approach for accurate end-diastolic frame detection in IVUS sequences is proposed, trained using electrocardiogram (ECG) signals acquired synchronously during IVUS acquisition. The framework integrates dedicated motion encoders and a bidirectional attention recurrent network (BARNet) with a temporal difference encoder to extract frame-by-frame motion features corresponding to the phases of the cardiac cycle. In addition, a spatiotemporal rotation encoder is included to capture the IVUS catheter's rotational movement with respect to the coronary artery. RESULTS: With a prediction tolerance range of 66.7 ms, the proposed approach was able to find 71.9%, 67.8%, and 69.9% of end-diastolic frames in the left anterior descending, left circumflex and right coronary arteries, respectively, when tested against ECG estimations. When the result was compared with two expert analysts’ estimation, the approach achieved a superior performance. DISCUSSION: These findings indicate that the developed methodology is accurate and fully reproducible and therefore it should be preferred over experts for end-diastolic frame detection in IVUS sequences

Formyl Peptide Receptor as a Novel Therapeutic Target for Anxiety-Related Disorders

Formyl peptide receptors (FPR) belong to a family of sensors of the immune system that detect microbe-associated molecules and inform various cellular and sensorial mechanisms to the presence of pathogens in the host. Here we demonstrate that Fpr2/3-deficient mice show a distinct profile of behaviour characterised by reduced anxiety in the marble burying and light-dark box paradigms, increased exploratory behaviour in an open-field, together with superior performance on a novel object recognition test. Pharmacological blockade with a formyl peptide receptor antagonist, Boc2, in wild type mice reproduced most of the behavioural changes observed in the Fpr2/3(-/-) mice, including a significant improvement in novel object discrimination and reduced anxiety in a light/dark shuttle test. These effects were associated with reduced FPR signalling in the gut as shown by the significant reduction in the levels of p-p38. Collectively, these findings suggest that homeostatic FPR signalling exerts a modulatory effect on anxiety-like behaviours. These findings thus suggest that therapies targeting FPRs may be a novel approach to ameliorate behavioural abnormalities present in neuropsychiatric disorders at the cognitive-emotional interface

Focusing and Compression of Ultrashort Pulses through Scattering Media

Light scattering in inhomogeneous media induces wavefront distortions which pose an inherent limitation in many optical applications. Examples range from microscopy and nanosurgery to astronomy. In recent years, ongoing efforts have made the correction of spatial distortions possible by wavefront shaping techniques. However, when ultrashort pulses are employed scattering induces temporal distortions which hinder their use in nonlinear processes such as in multiphoton microscopy and quantum control experiments. Here we show that correction of both spatial and temporal distortions can be attained by manipulating only the spatial degrees of freedom of the incident wavefront. Moreover, by optimizing a nonlinear signal the refocused pulse can be shorter than the input pulse. We demonstrate focusing of 100fs pulses through a 1mm thick brain tissue, and 1000-fold enhancement of a localized two-photon fluorescence signal. Our results open up new possibilities for optical manipulation and nonlinear imaging in scattering media

On dynamic network entropy in cancer

The cellular phenotype is described by a complex network of molecular interactions. Elucidating network properties that distinguish disease from the healthy cellular state is therefore of critical importance for gaining systems-level insights into disease mechanisms and ultimately for developing improved therapies. By integrating gene expression data with a protein interaction network to induce a stochastic dynamics on the network, we here demonstrate that cancer cells are characterised by an increase in the dynamic network entropy, compared to cells of normal physiology. Using a fundamental relation between the macroscopic resilience of a dynamical system and the uncertainty (entropy) in the underlying microscopic processes, we argue that cancer cells will be more robust to random gene perturbations. In addition, we formally demonstrate that gene expression differences between normal and cancer tissue are anticorrelated with local dynamic entropy changes, thus providing a systemic link between gene expression changes at the nodes and their local network dynamics. In particular, we also find that genes which drive cell-proliferation in cancer cells and which often encode oncogenes are associated with reductions in the dynamic network entropy. In summary, our results support the view that the observed increased robustness of cancer cells to perturbation and therapy may be due to an increase in the dynamic network entropy that allows cells to adapt to the new cellular stresses. Conversely, genes that exhibit local flux entropy decreases in cancer may render cancer cells more susceptible to targeted intervention and may therefore represent promising drug targets.Comment: 10 pages, 3 figures, 4 tables. Submitte

Spatial contrast sensitivity in adolescents with autism spectrum disorders

Adolescents with autism spectrum disorders (ASD) and typically developing (TD) controls underwent a rigorous psychophysical assessment that measured contrast sensitivity to seven spatial frequencies (0.5-20 cycles/degree). A contrast sensitivity function (CSF) was then fitted for each participant, from which four measures were obtained: visual acuity, peak spatial frequency, peak contrast sensitivity, and contrast sensitivity at a low spatial frequency. There were no group differences on any of the four CSF measures, indicating no differential spatial frequency processing in ASD. Although it has been suggested that detail-oriented visual perception in individuals with ASD may be a result of differential sensitivities to low versus high spatial frequencies, the current study finds no evidence to support this hypothesis