Feed-forward signaling by membrane-bound ligand receptor circuit: the case of NOTCH DELTA-like 4 ligand in endothelial cells

The DELTA like-4 ligand (DLL4) belongs to the highly conserved NOTCH family and is specifically expressed in the endothelium. DLL4 regulates crucial processes in vascular growth, including endothelial cell (EC) sprouting and arterial specification. Its expression is increased by VEGF-A. In the present study, we show that VEGF-induced DLL4 expression depends on NOTCH activation. VEGF-induced DLL4 expression was prevented by the blockage of NOTCH signaling with γ-secretase or ADAM inhibitors in human cardiac microvascular ECs. Similar to VEGF-A, recombinant DLL4 itself stimulated NOTCH signaling and resulted in up-regulation of DLL4, suggesting a positive feed-forward mechanism. These effects were abrogated by NOTCH inhibitors but not by inhibition of VEGF signaling. NOTCH activation alone suffices to induce DLL4 expression as illustrated by the positive effect of NOTCH intracellular domain (NICD)-1 or -4 overexpression. To discriminate between NICD/RBP-Jκ and FOXC2-regulated DLL4 expression, DLL4 promoter activity was assessed in promoter deletion experiments. NICD induced promoter activity was dependent on RBP-Jκ site but independent of the FOXC2 binding site. Accordingly, constitutively active FOXC2 did not affect DLL4 expression. The notion that the positive feed-forward mechanism might propagate NOTCH activation to neighboring ECs was supported by our observation that DLL4-eGFP-transfected ECs induced DLL4 expression in nontransfected cells in their vicinity. In summary, our data provide evidence for a mechanism by which VEGF or ligand-induced NOTCH signaling up-regulates DLL4 through a positive feed-forward mechanism. By this mechanism, DLL4 could propagate its own expression and enable synchronization of NOTCH expression and signaling between ECs.     

Temporal genetic samples indicate small effective population size of the endangered yellow-eyed penguin

There is an increasing awareness that the long-term viability of endemic island populations is negatively affected by genetic factors associated with population bottlenecks and/or persistence at small population size. Here we use contemporary samples and historic museum specimens (collected 1888–1938) to estimate the effective population size (N _e) for the endangered yellow-eyed penguin (Megadyptes antipodes) in South Island, New Zealand, and evaluate the genetic concern for this iconic species. The South Island population of M. antipodes—constituting almost half of the species’ census size—is thought to be descended from a small number of founders that reached New Zealand just a few hundred years ago. Despite intensive conservation measures, this population has shown dramatic fluctuations in size over recent decades. We compare estimates of the harmonic mean N _e for this population, obtained using one moment and three likelihood based-temporal methods, including one method that simultaneously estimates migration rate. Evaluation of the N _e estimates reveals a harmonic mean N _e in the low hundreds. Additionally, the inferred low immigration rates (m = 0.003) agree well with contemporary migration rate estimates between the South Island and subantarctic populations of M. antipodes. The low N _e of South Island M. antipodes is likely affected by strong fluctuations in population size, and high variance in reproductive success. These results show that genetic concerns for this population are valid and that the long-term viability of this species may be compromised by reduced adaptive potential.     

Reliable prediction of T-cell epitopes using neural networks with novel sequence representations

In this paper we describe an improved neural network method to predict T-cell class I epitopes. A novel input representation has been developed consisting of a combination of sparse encoding, Blosum encoding, and input derived from hidden Markov models. We demonstrate that the combination of several neural networks derived using different sequence-encoding schemes has a performance superior to neural networks derived using a single sequence-encoding scheme. The new method is shown to have a performance that is substantially higher than that of other methods. By use of mutual information calculations we show that peptides that bind to the HLA A*0204 complex display signal of higher order sequence correlations. Neural networks are ideally suited to integrate such higher order correlations when predicting the binding affinity. It is this feature combined with the use of several neural networks derived from different and novel sequence-encoding schemes and the ability of the neural network to be trained on data consisting of continuous binding affinities that gives the new method an improved performance. The difference in predictive performance between the neural network methods and that of the matrix-driven methods is found to be most significant for peptides that bind strongly to the HLA molecule, confirming that the signal of higher order sequence correlation is most strongly present in high-binding peptides. Finally, we use the method to predict T-cell epitopes for the genome of hepatitis C virus and discuss possible applications of the prediction method to guide the process of rational vaccine design.     

Trait variation in juvenile plants from the soil seed bank of temperate forests in relation to macro- and microclimate

Aim

The soil seed bank is a key component of the biodiversity of plant communities, but various aspects of its functioning in temperate forest ecosystems are still unknown. We here adopted a trait-based approach to investigate the effects of macro- and microclimatic gradients on the juvenile plant communities from the realized seed bank of two types of European temperate forest.

Location

Oak-dominated forests in Italy and Belgium.

Methods

We analysed the variation of key functional traits (plant height, leaf area, leaf dry weight, specific leaf area and leaf number) of juvenile plants from the realised soil seed bank in relation to elevation (from 0 to 800 m a.s.l.), forest type (thinned and unthinned forest) and distance to the forest edge. We translocated soil samples from the forest core to the edge (and vice versa) and from high- to low-elevation forests to test the effects of edge and warming respectively.

Results

Taller communities developed at the forest edge due to higher light availability and warmer temperatures. The translocation from the core to the edge did not significantly modify mean trait values. Instead, the shadier and cooler microclimate of the forest core reduced the mean leaf area, mean dry weight, height and leaf number in the communities realised from the edge soil. The translocation from high- to lowland forests led to increased values for all traits (except specific leaf area). Edge vs core trait variation was more driven by intraspecific variability, whereas the translocation from high- to low-elevation forests caused trait changes mostly due to species turnover.

Conclusions

Global warming might result in a functional shift of the understorey due to both an early filtering effect on the seedlings from soil seed banks and their adaptive trait adjustments to temperature increase. Furthermore, our study underpins the importance of edge vs core microclimate in driving the functional composition of the realised soil seed bank.     

Serum insulin-like growth factor I levels in growth hormone-deficient adults: influence of sex steroids

Measurement of serum insulin-like growth factor I (IGF-I) concentrations remains the single most important tool in the evaluation of growth hormone (GH) replacement in GH-deficient adults, and the therapeutic goal is to maintain the level within the age-adjusted normal range. In healthy adults, IGF-I levels do not differ between males and females, whereas spontaneous GH secretion is approximately twofold higher in females. Untreated GH-deficient women exhibit lower IGF-I levels compared with men, and the increase in serum IGF-I during GH replacement is also significantly less. Put together, these data suggest resistance to GH in women, which in healthy individuals is compensated for by increased GH secretion. Administration of oral oestrogen in healthy post-menopausal women suppresses hepatic IGF-I production and increases pituitary GH release, and oral oestrogen replacement in women with GH deficiency lowers IGF-I concentrations and increases the amount of GH necessary to obtain IGF-I target levels during treatment. These data clearly suggest that hepatic suppression of IGF-I production by oestrogen subserves the gender difference in GH sensitivity, but it is also likely that sex steroids may interact with the GH/IGF axis at further levels. There is also circumstantial evidence to indicate that testosterone stimulates IGF-I production, and it is speculated that a certain threshold level of androgens is essential to ensure hepatic IGF-I production. Whether these data should translate into earlier discontinuation of oestrogen replacement therapy in adult women with hypopituitarism merits consideration.     

Voluntarily controlled bi-stable slant perception of real and photographed surfaces

We have quantified voluntarily selected perceived slant of real trapezoidal surfaces (a 'reverse-perspective' scene) and their photographed counterparts (pictorial space). The surfaces were slanted about the vertical axis and observers estimated slant relative to the frontal plane. We were particularly interested in those cases in which binocular disparity and monocular perspective provided conflicting slant information. We varied the monocularly and binocularly specified surface slants independently across stimulus presentations. To eliminate texture and shading cues we used sand-blasted aluminium trapezoidal surfaces illuminated from all directions. When disparity-specified slant and perspective-specified slant were conflicting, observers were able to perceive the surfaces in two ways: they perceived either a trapezoid or a rectangle. Our main finding is twofold. First, when subjects chose to perceive the trapezoid, the slant estimates followed the disparity-predicted slant with only a slight underestimation, as if they selected a pure binocular representation of slant governed only by disparity. Second, when subjects chose to perceive the rectangle their estimates for real surfaces were similar to those for photographed surfaces, as if they selected a representation of slant governed by perspective foreshortening.     

Robust PCA and classification in biosciences

MOTIVATION: Principal components analysis (PCA) is a very popular dimension reduction technique that is widely used as a first step in the analysis of high-dimensional microarray data. However, the classical approach that is based on the mean and the sample covariance matrix of the data is very sensitive to outliers. Also, classification methods based on this covariance matrix do not give good results in the presence of outlying measurements. RESULTS: First, we propose a robust PCA (ROBPCA) method for high-dimensional data. It combines projection-pursuit ideas with robust estimation of low-dimensional data. We also propose a diagnostic plot to display and classify the outliers. This ROBPCA method is applied to several bio-chemical datasets. In one example, we also apply a robust discriminant method on the scores obtained with ROBPCA. We show that this combination of robust methods leads to better classifications than classical PCA and quadratic discriminant analysis. AVAILABILITY: All the programs are part of the Matlab Toolbox for Robust Calibration, available at http://www.wis.kuleuven.ac.be/stat/robust.html.     

BBLN-1 is essential for intermediate filament organization and apical membrane morphology

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The single-cell epigenomic and transcriptional landscape of immunity to influenza vaccination

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