PR1P, a VEGF-stabilizing peptide, reduces injury and inflammation in acute lung injury and ulcerative colitis animal models.

Acute Respiratory Distress Syndrome (ARDS) and Ulcerative Colitis (UC) are each characterized by tissue damage and uncontrolled inflammation. Neutrophils and other inflammatory cells play a primary role in disease progression by acutely responding to direct and indirect insults to tissue injury and by promoting inflammation through secretion of inflammatory cytokines and proteases. Vascular Endothelial Growth Factor (VEGF) is a ubiquitous signaling molecule that plays a key role in maintaining and promoting cell and tissue health, and is dysregulated in both ARDS and UC. Recent evidence suggests a role for VEGF in mediating inflammation, however, the molecular mechanism by which this occurs is not well understood. We recently showed that PR1P, a 12-amino acid peptide that binds to and upregulates VEGF, stabilizes VEGF from degradation by inflammatory proteases such as elastase and plasmin thereby limiting the production of VEGF degradation products (fragmented VEGF (fVEGF)). Here we show that fVEGF is a neutrophil chemoattractant in vitro and that PR1P can be used to reduce neutrophil migration in vitro by preventing the production of fVEGF during VEGF proteolysis. In addition, inhaled PR1P reduced neutrophil migration into airways following injury in three separate murine acute lung injury models including from lipopolysaccharide (LPS), bleomycin and acid. Reduced presence of neutrophils in the airways was associated with decreased pro-inflammatory cytokines (including TNF-α, IL-1ß, IL-6) and Myeloperoxidase (MPO) in broncho-alveolar lavage fluid (BALF). Finally, PR1P prevented weight loss and tissue injury and reduced plasma levels of key inflammatory cytokines IL-1ß and IL-6 in a rat TNBS-induced colitis model. Taken together, our data demonstrate that VEGF and fVEGF may each play separate and pivotal roles in mediating inflammation in ARDS and UC, and that PR1P, by preventing proteolytic degradation of VEGF and the production of fVEGF may represent a novel therapeutic approach to preserve VEGF signaling and inhibit inflammation in acute and chronic inflammatory diseases.

Breakdown of Random-Matrix Universality in Persistent Lotka-Volterra Communities.

The eigenvalue spectrum of a random matrix often only depends on the first and second moments of its elements, but not on the specific distribution from which they are drawn. The validity of this universality principle is often assumed without proof in applications. In this Letter, we offer a pertinent counterexample in the context of the generalized Lotka-Volterra equations. Using dynamic mean-field theory, we derive the statistics of the interactions between species in an evolved ecological community. We then show that the full statistics of these interactions, beyond those of a Gaussian ensemble, are required to correctly predict the eigenvalue spectrum and therefore stability. Consequently, the universality principle fails in this system. We thus show that the eigenvalue spectra of random matrices can be used to deduce the stability of "feasible" ecological communities, but only if the emergent non-Gaussian statistics of the interactions between species are taken into account.

Generalized Lotka-Volterra model with hierarchical interactions.

In the analysis of complex ecosystems it is common to use random interaction coefficients, which are often assumed to be such that all species are statistically equivalent. In this work we relax this assumption by imposing hierarchical interspecies interactions. These are incorporated into a generalized Lotka-Volterra dynamical system. In a hierarchical community species benefit more, on average, from interactions with species further below them in the hierarchy than from interactions with those above. Using dynamic mean-field theory, we demonstrate that a strong hierarchical structure is stabilizing, but that it reduces the number of species in the surviving community, as well as their abundances. Additionally, we show that increased heterogeneity in the variances of the interaction coefficients across positions in the hierarchy is destabilizing. We also comment on the structure of the surviving community and demonstrate that the abundance and probability of survival of a species are dependent on its position in the hierarchy.

Sampling rare trajectories using stochastic bridges.

The numerical quantification of the statistics of rare events in stochastic processes is a challenging computational problem. We present a sampling method that constructs an ensemble of stochastic trajectories that are constrained to have fixed start and end points (so-called stochastic bridges). We then show that by carefully choosing a set of such bridges and assigning an appropriate statistical weight to each bridge, one can focus more processing power on the rare events of a target stochastic process while faithfully preserving the statistics of these rare trajectories. Further, we also compare the stochastic bridges we produce to the Wentzel-Kramers-Brillouin (WKB) optimal paths of the target process, derived in the limit of low noise. We see that the generated paths, encoding the full statistics of the process, collapse onto the WKB optimal path as the level of noise is reduced. We propose that the method can also be used to judge the accuracy of the WKB approximation at finite levels of noise.

Eigenvalues of Random Matrices with Generalized Correlations: A Path Integral Approach.

Random matrix theory allows one to deduce the eigenvalue spectrum of a large matrix given only statistical information about its elements. Such results provide insight into what factors contribute to the stability of complex dynamical systems. In this Letter, we study the eigenvalue spectrum of an ensemble of random matrices with correlations between any pair of elements. To this end, we introduce an analytical method that maps the resolvent of the random matrix onto the response functions of a linear dynamical system. The response functions are then evaluated using a path integral formalism, enabling us to make deductions about the eigenvalue spectrum. Our central result is a simple, closed-form expression for the leading eigenvalue of a large random matrix with generalized correlations. This formula demonstrates that correlations between matrix elements that are not diagonally opposite, which are often neglected, can have a significant impact on stability.

Analytical and Numerical Treatment of Continuous Ageing in the Voter Model.

The conventional voter model is modified so that an agent's switching rate depends on the 'age' of the agent-that is, the time since the agent last switched opinion. In contrast to previous work, age is continuous in the present model. We show how the resulting individual-based system with non-Markovian dynamics and concentration-dependent rates can be handled both computationally and analytically. The thinning algorithm of Lewis and Shedler can be modified in order to provide an efficient simulation method. Analytically, we demonstrate how the asymptotic approach to an absorbing state (consensus) can be deduced. We discuss three special cases of the age-dependent switching rate: one in which the concentration of voters can be approximated by a fractional differential equation, another for which the approach to consensus is exponential in time, and a third case in which the system reaches a frozen state instead of consensus. Finally, we include the effects of a spontaneous change of opinion, i.e., we study a noisy voter model with continuous ageing. We demonstrate that this can give rise to a continuous transition between coexistence and consensus phases. We also show how the stationary probability distribution can be approximated, despite the fact that the system cannot be described by a conventional master equation.

Eigenvalue spectra and stability of directed complex networks.

Quantifying the eigenvalue spectra of large random matrices allows one to understand the factors that contribute to the stability of dynamical systems with many interacting components. This work explores the effect that the interaction network between components has on the eigenvalue spectrum. We build on previous results, which usually only take into account the mean degree of the network, by allowing for nontrivial network degree heterogeneity. We derive closed-form expressions for the eigenvalue spectrum of the adjacency matrix of a general weighted and directed network. Using these results, which are valid for any large well-connected complex network, we then derive compact formulas for the corrections (due to nonzero network heterogeneity) to well-known results in random matrix theory. Specifically, we derive modified versions of the Wigner semicircle law, the Girko circle law, and the elliptic law and any outlier eigenvalues. We also derive a surprisingly neat analytical expression for the eigenvalue density of a directed Barabási-Albert network. We are thus able to deduce that network heterogeneity is mostly a destabilizing influence in complex dynamical systems.

Consensus, polarization, and coexistence in a continuous opinion dynamics model with quenched disorder.

A model of opinion dynamics is introduced in which each individual's opinion is measured on a bounded continuous spectrum. Each opinion is influenced heterogeneously by every other opinion in the population. It is demonstrated that consensus, polarization and a spread of moderate opinions are all possible within this model. Using dynamic mean-field theory, we are able to identify the statistical features of the interactions between individuals that give rise to each of the aforementioned emergent phenomena. The nature of the transitions between each of the observed macroscopic states is also studied. It is demonstrated that heterogeneity of interactions between individuals can lead to polarization, that mostly antagonistic or contrarian interactions can promote consensus at a moderate opinion, and that mostly reinforcing interactions encourage the majority to take an extreme opinion.

Persistent individual bias in a voter model with quenched disorder.

Many theoretical studies of the voter model (or variations thereupon) involve order parameters that are population-averaged. While enlightening, such quantities may obscure important statistical features that are only apparent on the level of the individual. In this work, we ask which factors contribute to a single voter maintaining a long-term statistical bias for one opinion over the other in the face of social influence. To this end, a modified version of the network voter model is proposed, which also incorporates quenched disorder in the interaction strengths between individuals and the possibility of antagonistic relationships. We find that a sparse interaction network and heterogeneity in interaction strengths give rise to the possibility of arbitrarily long-lived individual biases, even when there is no population-averaged bias for one opinion over the other. This is demonstrated by calculating the eigenvalue spectrum of the weighted network Laplacian using the theory of sparse random matrices.

Dispersal-induced instability in complex ecosystems.

In his seminal work in the 1970s, Robert May suggested that there is an upper limit to the number of species that can be sustained in stable equilibrium by an ecosystem. This deduction was at odds with both intuition and the observed complexity of many natural ecosystems. The so-called stability-diversity debate ensued, and the discussion about the factors contributing to ecosystem stability or instability continues to this day. We show in this work that dispersal can be a destabilising influence. To do this, we combine ideas from Alan Turing's work on pattern formation with May's random-matrix approach. We demonstrate how a stable equilibrium in a complex ecosystem with trophic structure can become unstable with the introduction of dispersal in space, and we discuss the factors which contribute to this effect. Our work highlights that adding more details to the model of May can give rise to more ways for an ecosystem to become unstable. Making May's simple model more realistic is therefore unlikely to entirely remove the upper bound on complexity.

Intrinsic noise, Delta-Notch signalling and delayed reactions promote sustained, coherent, synchronized oscillations in the presomitic mesoderm.

Using a stochastic individual-based modelling approach, we examine the role that Delta-Notch signalling plays in the regulation of a robust and reliable somite segmentation clock. We find that not only can Delta-Notch signalling synchronize noisy cycles of gene expression in adjacent cells in the presomitic mesoderm (as is known), but it can also amplify and increase the coherence of these cycles. We examine some of the shortcomings of deterministic approaches to modelling these cycles and demonstrate how intrinsic noise can play an active role in promoting sustained oscillations, giving rise to noise-induced quasi-cycles. Finally, we explore how translational/transcriptional delays can result in the cycles in neighbouring cells oscillating in anti-phase and we study how this effect relates to the propagation of noise-induced stochastic waves.

Stochastic fluctuations and quasipattern formation in reaction-diffusion systems with anomalous transport.

Many approaches to modeling reaction-diffusion systems with anomalous transport rely on deterministic equations which ignore fluctuations arising due to finite particle numbers. Starting from an individual-based model we use a generating-functional approach to derive a Gaussian approximation for this intrinsic noise in subdiffusive systems. This results in corrections to the deterministic fractional reaction-diffusion equations. Using this analytical approach, we study the onset of noise-driven quasipatterns in reaction-subdiffusion systems. We find that subdiffusion can be conducive to the formation of both deterministic and stochastic patterns. Our analysis shows that the combination of subdiffusion and intrinsic stochasticity can reduce the threshold ratio of the effective diffusion coefficients required for pattern formation to a greater degree than either effect on its own.

Effective diffusion coefficients in reaction-diffusion systems with anomalous transport.

We show that the Turing patterns in reaction systems with subdiffusion can be replicated in an effective system with Markovian cross-diffusion. The effective system has the same Turing instability as the original system and the same patterns. If particles are short lived, then the transient dynamics are captured as well. We use the cross-diffusive system to define effective diffusion coefficients for the system with anomalous transport, and we show how they can be used to efficiently describe the Turing instability. We also demonstrate that the mean-squared displacement of a suitably defined ensemble of subdiffusing particles grows linearly with time, with a diffusion coefficient which agrees with our earlier calculations. We verify these deductions by numerically integrating both the fractional reaction-diffusion equation and its normally diffusing counterpart. Our findings suggest that cross-diffusive behavior can come about as a result of anomalous transport.

How successful are mutants in multiplayer games with fluctuating environments? Sojourn times, fixation and optimal switching.

Using a stochastic model, we investigate the probability of fixation, and the average time taken to achieve fixation, of a mutant in a population of wild-types. We do this in a context where the environment in which the competition takes place is subject to stochastic change. Our model takes into account interactions which can involve multiple participants. That is, the participants take part in multiplayer games. We find that under certain circumstances, there are environmental switching dynamics which minimize the time that it takes for the mutants to fixate. To analyse the dynamics more closely, we develop a method by which to calculate the sojourn times for general birth-death processes in fluctuating environments.

Quercetin Therapy for Selected Patients with PIM1 Kinase-Positive Chronic Lymphocytic Leukemia/Small Lymphocytic Lymphoma: A Pilot Study.

We reported that PIM1 kinase is expressed in the lymphocytes of patients with chronic lymphocytic leukemia (CLL)/small lymphocytic lymphoma (SLL). Quercetin, a naturally occurring flavonoid, is a dietary supplement and inhibits many kinases, including PIM1, in vitro. Under an Institutional Review Board-approved protocol, we performed an open-label, single-arm pilot study to evaluate the antitumor activity of quercetin in patients with CLL/SLL. Q-ForceTM chews were administered orally, 500 mg twice daily, for 3 months. Eligible patients had failed prior therapies, had had no other standard treatment, or refused other therapies. Response was assessed based on objective change in disease parameters. Patients were included if their lymphocyte counts were rising and ≥10,000/µL but not > 100,000/µL. Three patients received quercetin treatment. There was no toxicity. Two responded with stabilization of rising lymphocyte counts (p < 0.001 for each), which remained stable during their follow-up (5 and 11 months after cessation of treatment, respectively). The CLL cells in the nonresponder harbored a TP53 mutation. Although our data from this pilot translational study are based on a small sample, further studies of quercetin as a potential therapeutic agent in selected patients with CLL/SLL appear warranted.

Patients with cranial dural arteriovenous fistulas may benefit from expanded hypercoagulability and cancer screening.

OBJECTIVE: Cranial dural arteriovenous fistulas (DAVFs) have been associated with dural sinus occlusion, and previous reports have suggested the association of hypercoagulability with some cases. But the prevalence of a hypercoagulable state has not been systematically analyzed in conjunction with laboratory markers and clinical manifestations, including history of thromboembolism or systemic malignancy. The authors hypothesize that laboratory or clinical evidence of a hypercoagulable state, including cancer, is commonly identifiable in consecutively identified patients with DAVFs, with implications for clinical management. METHODS: The retrospective cohort study included all patients older than 17 years with cranial DAVFs diagnosed at University of Chicago Medicine during a 6-year period, whose medical records and imaging results were reviewed for objective laboratory or clinical evidence of a hypercoagulable state, including malignancy. Each case was analyzed for implications on clinical management. Data were analyzed in relation to a systematic review of the literature on this association. RESULTS: Fifteen (88%) of 17 cases of DAVFs had laboratory (n = 8) or clinical evidence of a hypercoagulable state (thromboembolism [n = 8] or cancer [n = 6]). This hypercoagulability or cancer impacted clinical care in all 15 cases. CONCLUSIONS: An underlying hypercoagulable state manifested by laboratory testing or clinically, including cancer, is staggeringly common. It is important to recognize this association, along with its impact on the management of the DAVFs and systemic diseases.

The Relationship between RUVBL1 (Pontin, TIP49, NMP238) and BCL6 in Benign and Malignant Human Lymphoid Tissues.

The human BCL6 gene, which is involved in the pathogenesis of certain human lymphomas, encodes a transcriptional repressor that is needed for germinal center B cell development and T follicular helper cell differentiation. Our goal was to identify BCL6 target genes using a cell system in which BCL6 repressive effects are inhibited followed by subtractive hybridization, and we detected the RUVBL1 (Pontin, TIP49) gene as a potential target of BCL6 repression. Here we show that the BCL6 protein significantly represses RUVBL1 transcription (6.8-fold). Knockdown of endogenous BCL6 in a human B cell lymphoma line leads to significant upregulation of RUVBL1, and there is an inverse expression pattern between the BCL6 and RUVBL1 proteins in certain human lymphomas. RUVBL1 is part of the AAA+ superfamily and participates in multiple processes, including gene transcription regulation, chromatin remodeling, and DNA repair, which, if dysregulated, may promote lymphoma development. A further understanding of the relationship between RUVBL1 and BCL6 should improve our understanding of the pathogenesis of human lymphomas.

The ITM2B (BRI2) gene is a target of BCL6 repression: Implications for lymphomas and neurodegenerative diseases.

The human BCL6 gene encodes a transcriptional repressor that is crucial for germinal center B cell development and T follicular helper cell differentiation. It is involved in the pathogenesis of certain human lymphomas. In an effort to identify targets of BCL6 repression, we used a previously described cell system in which BCL6 repressive effects are inhibited, followed by subtractive hybridization, and identified the integral membrane 2B gene (ITM2B, formerly BRI2) as a potential target. Here we show that BCL6 can bind to its preferential consensus binding site within the first intron of ITM2B and represses its transcription. Knockdown of endogenous BCL6 in a human B cell lymphoma line increases ITM2B expression. Further, there is an inverse relationship between the expression levels of BCL6 and ITM2B proteins in 16 human B- and T-cell lymphomas studied by immunohistochemistry. Both the BCL6 and ITM2B proteins are expressed ubiquitously. Similar to some other targets of BCL6, a short form of the ITM2B protein generated by alternative splicing induces apoptosis in hematopoietic cell lines. Molecular alterations in the ITM2B gene are associated with two neurodegenerative diseases, Familial British and Familial Danish dementia. ITM2B dysfunction also may be relevant for the development of Alzheimer's disease. Our data confirm ITM2B as a target of BCL6 repression in lymphoma. A further understanding of the genes that function as regulators of the ITM2B protein may provide insights for the development of new molecular tools not only for targeted lymphoma therapy but also for the treatment of these dementias.