Delivery of AAV2/9-microdystrophin genes incorporating helix 1 of the coiled-coil motif in the C-terminal domain of dystrophin improves muscle pathology and restores the level of α1-syntrophin and α-dystrobrevin in skeletal muscles of mdx mice. Level of α1-Syntrophin and α-Dystrobrevin in Skeletal Muscles of mdx Mice

Duchenne muscular dystrophy is a severe X-linked inherited muscle wasting disorder caused by mutations in the dystrophin gene. Adeno-associated virus (AAV) vectors have been extensively used to deliver genes efficiently for dystrophin expression in skeletal muscles. To overcome limited packaging capacity of AAV vectors (<5 kb), truncated recombinant microdystrophin genes with deletions of most of rod and carboxyl-terminal (CT) domains of dystrophin have been developed. We have previously shown the efficiency of mRNA sequence–optimized microdystrophin (ΔR4-23/ΔCT, called MD1) with deletion of spectrin-like repeat domain 4 to 23 and CT domain in ameliorating the pathology of dystrophic mdx mice. However, the CT domain of dystrophin is thought to recruit part of the dystrophin-associated protein complex, which acts as a mediator of signalling between extracellular matrix and cytoskeleton in muscle fibers. In this study, we extended the ΔR4-23/ΔCT microdystrophin by incorporating helix 1 of the coiled-coil motif in the CT domain of dystrophin (MD2), which contains the α1-syntrophin and α-dystrobrevin binding sites. Intramuscular injection of AAV2/9 expressing CT domain–extended microdystrophin showed efficient dystrophin expression in tibialis anterior muscles of mdx mice. The presence of the CT domain of dystrophin in MD2 increased the recruitment of α1-syntrophin and α-dystrobrevin at the sarcolemma and significantly improved the muscle resistance to lengthening contraction–induced muscle damage in the mdx mice compared with MD1. These results suggest that the incorporation of helix 1 of the coiled-coil motif in the CT domain of dystrophin to the microdystrophins will substantially improve their efficiency in restoring muscle function in patients with Duchenne muscular dystrophy.

Self-assembly and bioactivity of a polymer/peptide conjugate containing the RGD cell adhesion motif and PEG

The self-assembly and bioactivity of the peptide–polymer conjugate DGRFFF–PEG3000 containing the RGD cell adhesion motif has been examined, in aqueous solution. The conjugate is designed to be amphiphilic by incorporation of three hydrophobic phenylalanine residues as well as the RGD unit and a short poly(ethylene glycol) (PEG) chain of molar mass 3000 kg mol-1. Above a critical aggregation concentration, determined by fluorescence measurements, signals of b-sheet structure are revealed by spectroscopic measurements, as well as X-ray diffraction. At high concentration, a self-assembled fibril nanostructure is revealed by electron microscopy. The fibrils are observed despite PEG crystallization which occurs on drying. This suggests that DGRFFF has an aggregation tendency that is sufficiently strong not to be prevented by PEG crystallization. The adhesion, viability and proliferation of human corneal fibroblasts was examined for films of the conjugate on tissue culture plates (TCPs) as well as low attachment plates. On TCP, DGRFFF–PEG3000 films prepared at sufficiently low concentration are viable, and cell proliferation is observed. However, on low attachment surfaces, neither cell adhesion nor proliferation was observed, indicating that the RGD motif was not available to enhance cell adhesion. This was ascribed to the core–shell architecture of the self-assembled fibrils with a peptide core surrounded by a PEG shell which hinders access to the RGD unit.

Alanine-rich amphiphilic peptide containing the RGD cell adhesion motif: a coating material for human fibroblast attachment and culture

We studied the self-assembly of peptide A6RGD (A: alanine, R: arginine, G: glycine, D: aspartic acid) in water, and the use of A6RGD substrates as coatings to promote the attachment of human cornea stromal fibroblasts (hCSFs). The self-assembled motif of A6RGD was shown to depend on the peptide concentration in water, where both vesicle and fibril formation were observed. Oligomers were detected for 0.7 wt% A6RGD, which evolved into short peptide fibres at 1.0 wt% A6RGD, while a co-existence of vesicles and long peptide fibres was revealed for 2–15 wt% A6RGD. A6RGD vesicle walls were shown to have a multilayer structure built out of highly interdigitated A6 units, while A6RGD fibres were based on β-sheet assemblies. Changes in the self-assembly motif with concentration were reflected in the cell culture assay results. Films dried from 0.1–1.0 wt% A6RGD solutions allowed hCSFs to attach and significantly enhanced cell proliferation relative to the control. In contrast, films dried from 2.5 wt% A6RGD solutions were toxic to hCSFs.

The mirror neuron system as revealed through neonatal imitation: presence from birth, predictive power, and evidence of plasticity

There is strong evidence that neonates imitate previously unseen behaviors. These behaviors are predominantly used in social interactions, demonstrating neonates’ ability and motivation to engage with others. Research on neonatal imitation can provide a wealth of information about the early mirror neuron system (MNS): namely, its functional characteristics, its plasticity from birth, and its relation to skills later in development. Though numerous studies document the existence of neonatal imitation in the laboratory, little is known about its natural occurrence during parent-infant interactions and its plasticity as a consequence of experience. We review these critical aspects of imitation, which we argue are necessary for understanding the early action-perception system. We address common criticisms and misunderstandings about neonatal imitation and discuss methodological differences among studies. Recent work reveals that individual differences in neonatal imitation positively correlate with later social, cognitive, and motor development. We propose that such variation in neonatal imitation could reflect important individual differences of the MNS. Although postnatal experience is not necessary for imitation, we present evidence that neonatal imitation is influenced by experience in the first week of life.

Humans use predictive kinematic models to calibrate visual cues to three-dimensional surface slant

When the sensory consequences of an action are systematically altered our brain can recalibrate the mappings between sensory cues and properties of our environment. This recalibration can be driven by both cue conflicts and altered sensory statistics, but neither mechanism offers a way for cues to be calibrated so they provide accurate information about the world, as sensory cues carry no information as to their own accuracy. Here, we explored whether sensory predictions based on internal physical models could be used to accurately calibrate visual cues to 3D surface slant. Human observers played a 3D kinematic game in which they adjusted the slant of a surface so that a moving ball would bounce off the surface and through a target hoop. In one group, the ball’s bounce was manipulated so that the surface behaved as if it had a different slant to that signaled by visual cues. With experience of this altered bounce, observers recalibrated their perception of slant so that it was more consistent with the assumed laws of kinematics and physical behavior of the surface. In another group, making the ball spin in a way that could physically explain its altered bounce eliminated this pattern of recalibration. Importantly, both groups adjusted their behavior in the kinematic game in the same way, experienced the same set of slants and were not presented with low-level cue conflicts that could drive the recalibration. We conclude that observers use predictive kinematic models to accurately calibrate visual cues to 3D properties of world.

Towards cost-sensitive adaptation: when is it worth updating your predictive model?

Our digital universe is rapidly expanding,more and more daily activities are digitally recorded, data arrives in streams, it needs to be analyzed in real time and may evolve over time. In the last decade many adaptive learning algorithms and prediction systems, which can automatically update themselves with the new incoming data, have been developed. The majority of those algorithms focus on improving the predictive performance and assume that model update is always desired as soon as possible and as frequently as possible. In this study we consider potential model update as an investment decision, which, as in the financial markets, should be taken only if a certain return on investment is expected. We introduce and motivate a new research problem for data streams ? cost-sensitive adaptation. We propose a reference framework for analyzing adaptation strategies in terms of costs and benefits. Our framework allows to characterize and decompose the costs of model updates, and to asses and interpret the gains in performance due to model adaptation for a given learning algorithm on a given prediction task. Our proof-of-concept experiment demonstrates how the framework can aid in analyzing and managing adaptation decisions in the chemical industry.

Interactions between lipid-free apolipoprotein-AI and a lipopeptide incorporating the RGDS cell adhesion motif

The interaction of a designed bioactive lipopeptide C16-GGGRGDS, comprising a hexadecyl lipid chain attached to a functional heptapeptide, with the lipid-free apoliprotein, Apo-AI, is examined. This apolipoprotein is a major component of high density lipoprotein and it is involved in lipid metabolism and may serve as a biomarker for cardiovascular disease and Alzheimers’ disease. We find via isothermal titration calorimetry that binding between the lipopeptide and Apo-AI occurs up to a saturation condition, just above equimolar for a 10.7 μM concentration of Apo-AI. A similar value is obtained from circular dichroism spectroscopy, which probes the reduction in α-helical secondary structure of Apo-AI upon addition of C16-GGGRGDS. Electron microscopy images show a persistence of fibrillar structures due to self-assembly of C16-GGGRGDS in mixtures with Apo-AI above the saturation binding condition. A small fraction of spheroidal or possibly “nanodisc” structures was observed. Small-angle X-ray scattering (SAXS) data for Apo-AI can be fitted using a published crystal structure of the Apo-AI dimer. The SAXS data for the lipopeptide/ Apo-AI mixtures above the saturation binding conditions can be fitted to the contribution from fibrillar structures coexisting with flat discs corresponding to Apo-AI/lipopeptide aggregates.

The importance of loop length on the stability of i-motif structures

Using UV and srCD spectroscopy it is found that loop length within the i-motif structure is important for both thermal and pH stability, but in contrast to previous statements, it is the shorter loops that exhibit the highest stability.

On the predictive content of leading indicators: the case of U.S. real estate markets

This paper employs a probit and a Markov switching model using information from the Conference Board Leading Indicator and other predictor variables to forecast the signs of future rental growth in four key U.S. commercial rent series. We find that both approaches have considerable power to predict changes in the direction of commercial rents up to two years ahead, exhibiting strong improvements over a naïve model, especially for the warehouse and apartment sectors. We find that while the Markov switching model appears to be more successful, it lags behind actual turnarounds in market outcomes whereas the probit is able to detect whether rental growth will be positive or negative several quarters ahead.

Stabilization of the i-motif structure by the intra-strand cross-link formation

The i-motif structures are formed by oligonucleotides containing cytosine tracts under acidic conditions. The folding of the i-motif under physiological conditions is of great interest because of its biological role. In this study, we investigated the effect of the intra-strand cross-link on the stability of the i-motif structure. The 4-vinyl-substituted analog of thymidine (T-vinyl) was incorporated into the 5′-end of the human telomere complementary strand, which formed the intra-strand cross-link with the internal adenine. The intra-strand cross-linked i-motif displayed CD spectra similar to that of the natural i-motif at acidic pH, which was transformed into a random coil with the increasing pH. The pH midpoint for the transition from the i-motif to random coil increased from pH 6.1 for the natural one to pH 6.8 for the cross-linked one. The thermodynamic parameters were obtained by measuring the thermal melting behaviors by CD and UV, and it was determined that the intra-strand cross-linked i-motif is stabilized due to a favorable entropy effect. Thus, this study has clearly indicated the validity of the intra-strand cross-linking for stabilization of the i-motif structure.

Growth factor receptor-bound protein 2 contributes to (hem)immunoreceptor tyrosine-based activation motif-mediated signaling in platelets

Rationale: Platelets are anuclear cell fragments derived from bone marrow megakaryocytes (MKs) that safeguard vascular integrity but may also cause pathological vessel occlusion. One major pathway of platelet activation is triggered by 2 receptors that signal through an (hem)immunoreceptor tyrosine-based activation motif (ITAM), the activating collagen receptor glycoprotein (GP) VI and the C-type lectin-like receptor 2 (CLEC-2). Growth factor receptor–bound protein 2 (Grb2) is a ubiquitously expressed adapter molecule involved in signaling processes of numerous receptors in different cell types, but its function in platelets and MKs is unknown. Objective: We tested the hypothesis that Grb2 is a crucial adapter protein in (hem)immunoreceptor tyrosine-based activation motif signaling in platelets. Methods and Results: Here, we show that genetic ablation of Grb2 in MKs and platelets did not interfere with MK differentiation or platelet production. However, Grb2-deficiency severely impaired glycoprotein VI–mediated platelet activation because of defective stabilization of the linker of activated T-cell (LAT) signalosome and activation of downstream signaling proteins that resulted in reduced adhesion, aggregation, and coagulant activity on collagen in vitro. Similarly, CLEC-2–mediated signaling was impaired in Grb2-deficient platelets, whereas the cells responded normally to stimulation of G protein–coupled receptors. In vivo, this selective (hem)immunoreceptor tyrosine-based activation motif signaling defect resulted in prolonged bleeding times but affected arterial thrombus formation only after concomitant treatment with acetylsalicylic acid, indicating that defective glycoprotein VI signaling in the absence of Grb2 can be compensated through thromboxane A2–induced G protein–coupled receptor signaling pathways. Conclusions: These results reveal an important contribution of Grb2 in (hem)immunoreceptor tyrosine-based activation motif signaling in platelets in hemostasis and thrombosis by stabilizing the LAT signalosome.

Critical role for an acidic amino acid region in platelet signaling by the HemITAM (hemi-immunoreceptor tyrosine-based activation motif) containing receptor CLEC-2 (C-type lectin receptor-2)

CLEC-2 is a member of new family of C-type lectin receptors characterized by a cytosolic YXXL downstream of three acidic amino acids in a sequence known as a hemITAM (hemi-immunoreceptor tyrosine-based activation motif). Dimerization of two phosphorylated CLEC-2 molecules leads to recruitment of the tyrosine kinase Syk via its tandem SH2 domains and initiation of a downstream signaling cascade. Using Syk-deficient and Zap-70-deficient cell lines we show that hemITAM signaling is restricted to Syk and that the upstream triacidic amino acid sequence is required for signaling. Using surface plasmon resonance and phosphorylation studies, we demonstrate that the triacidic amino acids are required for phosphorylation of the YXXL. These results further emphasize the distinct nature of the proximal events in signaling by hemITAM relative to ITAM receptors.

Syk-dependent phosphorylation of CLEC-2: a novel mechanism of hem-immunoreceptor tyrosine-based activation motif signalling

The C-type lectin-like receptor CLEC-2 signals via phosphorylation of a single cytoplasmic YXXL sequence known as a hem-immunoreceptor tyrosine-based activation motif (hemITAM). In this study, we show that phosphorylation of CLEC-2 by the snake toxin rhodocytin is abolished in the absence of the tyrosine kinase Syk but is not altered in the absence of the major platelet Src family kinases, Fyn, Lyn, and Src, or the tyrosine phosphatase CD148, which regulates the basal activity of Src family kinases. Further, phosphorylation of CLEC-2 by rhodocytin is not altered in the presence of the Src family kinase inhibitor PP2, even though PLCγ2 phosphorylation and platelet activation are abolished. A similar dependence of phosphorylation of CLEC-2 on Syk is also seen in response to stimulation by an IgG mAb to CLEC-2, although interestingly CLEC-2 phosphorylation is also reduced in the absence of Lyn. These results provide the first definitive evidence that Syk mediates phosphorylation of the CLEC-2 hemITAM receptor with Src family kinases playing a critical role further downstream through the regulation of Syk and other effector proteins, providing a new paradigm in signaling by YXXL-containing receptors.

Testing projected wild bee distributions in agricultural habitats: predictive power depends on species traits and habitat type

Species distribution models (SDM) are increasingly used to understand the factors that regulate variation in biodiversity patterns and to help plan conservation strategies. However, these models are rarely validated with independently collected data and it is unclear whether SDM performance is maintained across distinct habitats and for species with different functional traits. Highly mobile species, such as bees, can be particularly challenging to model. Here, we use independent sets of occurrence data collected systematically in several agricultural habitats to test how the predictive performance of SDMs for wild bee species depends on species traits, habitat type, and sampling technique. We used a species distribution modeling approach parametrized for the Netherlands, with presence records from 1990 to 2010 for 193 Dutch wild bees. For each species, we built a Maxent model based on 13 climate and landscape variables. We tested the predictive performance of the SDMs with independent datasets collected from orchards and arable fields across the Netherlands from 2010 to 2013, using transect surveys or pan traps. Model predictive performance depended on species traits and habitat type. Occurrence of bee species specialized in habitat and diet was better predicted than generalist bees. Predictions of habitat suitability were also more precise for habitats that are temporally more stable (orchards) than for habitats that suffer regular alterations (arable), particularly for small, solitary bees. As a conservation tool, SDMs are best suited to modeling rarer, specialist species than more generalist and will work best in long-term stable habitats. The variability of complex, short-term habitats is difficult to capture in such models and historical land use generally has low thematic resolution. To improve SDMs’ usefulness, models require explanatory variables and collection data that include detailed landscape characteristics, for example, variability of crops and flower availability. Additionally, testing SDMs with field surveys should involve multiple collection techniques.

Towards predictive understanding of regional climate change

Regional information on climate change is urgently needed but often deemed unreliable. To achieve credible regional climate projections, it is essential to understand underlying physical processes, reduce model biases and evaluate their impact on projections, and adequately account for internal variability. In the tropics, where atmospheric internal variability is small compared with the forced change, advancing our understanding of the coupling between long-term changes in upper-ocean temperature and the atmospheric circulation will help most to narrow the uncertainty. In the extratropics, relatively large internal variability introduces substantial uncertainty, while exacerbating risks associated with extreme events. Large ensemble simulations are essential to estimate the probabilistic distribution of climate change on regional scales. Regional models inherit atmospheric circulation uncertainty from global models and do not automatically solve the problem of regional climate change. We conclude that the current priority is to understand and reduce uncertainties on scales greater than 100 km to aid assessments at finer scales.