A G-protein-coupled chemoattractant receptor recognizes lipopolysaccharide for bacterial phagocytosis.

Phagocytes locate microorganisms via chemotaxis and then consume them using phagocytosis. Dictyostelium amoebas are stereotypical phagocytes that prey on diverse bacteria using both processes. However, as typical phagocytic receptors, such as complement receptors or Fcγ receptors, have not been found in Dictyostelium, it remains mysterious how these cells recognize bacteria. Here, we show that a single G-protein-coupled receptor (GPCR), folic acid receptor 1 (fAR1), simultaneously recognizes the chemoattractant folate and the phagocytic cue lipopolysaccharide (LPS), a major component of bacterial surfaces. Cells lacking fAR1 or its cognate G-proteins are defective in chemotaxis toward folate and phagocytosis of Klebsiella aerogenes. Computational simulations combined with experiments show that responses associated with chemotaxis can also promote engulfment of particles coated with chemoattractants. Finally, the extracellular Venus-Flytrap (VFT) domain of fAR1 acts as the binding site for both folate and LPS. Thus, fAR1 represents a new member of the pattern recognition receptors (PRRs) and mediates signaling from both bacterial surfaces and diffusible chemoattractants to reorganize actin for chemotaxis and phagocytosis.

Tools for Economic Analysis of Patient Management Interventions in Heart Failure Cost-Effectiveness Model: A Web-based program designed to evaluate the cost-effectiveness of disease management programs in heart failure.

BACKGROUND: Heart failure disease management programs can influence medical resource use and quality-adjusted survival. Because projecting long-term costs and survival is challenging, a consistent and valid approach to extrapolating short-term outcomes would be valuable. METHODS: We developed the Tools for Economic Analysis of Patient Management Interventions in Heart Failure Cost-Effectiveness Model, a Web-based simulation tool designed to integrate data on demographic, clinical, and laboratory characteristics; use of evidence-based medications; and costs to generate predicted outcomes. Survival projections are based on a modified Seattle Heart Failure Model. Projections of resource use and quality of life are modeled using relationships with time-varying Seattle Heart Failure Model scores. The model can be used to evaluate parallel-group and single-cohort study designs and hypothetical programs. Simulations consist of 10,000 pairs of virtual cohorts used to generate estimates of resource use, costs, survival, and incremental cost-effectiveness ratios from user inputs. RESULTS: The model demonstrated acceptable internal and external validity in replicating resource use, costs, and survival estimates from 3 clinical trials. Simulations to evaluate the cost-effectiveness of heart failure disease management programs across 3 scenarios demonstrate how the model can be used to design a program in which short-term improvements in functioning and use of evidence-based treatments are sufficient to demonstrate good long-term value to the health care system. CONCLUSION: The Tools for Economic Analysis of Patient Management Interventions in Heart Failure Cost-Effectiveness Model provides researchers and providers with a tool for conducting long-term cost-effectiveness analyses of disease management programs in heart failure.

Associations between seattle heart failure model scores and medical resource use and costs: findings from HF-ACTION.

BACKGROUND: Prognostic models, such as the Seattle Heart Failure Model (SHFM), have been developed to predict patient survival. The extent to which they predict medical resource use and costs has not been explored. In this study, we evaluated relationships between baseline SHFM scores and 1-year resource use and costs using data from a clinical trial. METHODS AND RESULTS: We applied generalized linear models to examine the relative impact of a 1-unit increase in SHFM scores on counts of medical resource use and direct medical costs at 1 year of follow-up. Of 2331 randomized patients, 2288 (98%) had a rounded integer SHFM score between -1 and 2, consistent with predicted 1-year survival of 98% and 74%, respectively. At baseline, median age was 59 years, 28% of patients were women, and nearly two-thirds of the cohort had New York Heart Association class II heart failure and one-third had class III heart failure. Higher SHFM scores were associated with more hospitalizations (rate ratio per 1-unit increase, 1.86; P < .001), more inpatient days (2.30; P < .001), and higher inpatient costs (2.28; P < .001), outpatient costs (1.54; P < .001), and total medical costs (2.13; P < .001). CONCLUSION: Although developed to predict all-cause mortality, SHFM scores also predict medical resource use and costs.

Chemotaxis: a feedback-based computational model robustly predicts multiple aspects of real cell behaviour.

The mechanism of eukaryotic chemotaxis remains unclear despite intensive study. The most frequently described mechanism acts through attractants causing actin polymerization, in turn leading to pseudopod formation and cell movement. We recently proposed an alternative mechanism, supported by several lines of data, in which pseudopods are made by a self-generated cycle. If chemoattractants are present, they modulate the cycle rather than directly causing actin polymerization. The aim of this work is to test the explanatory and predictive powers of such pseudopod-based models to predict the complex behaviour of cells in chemotaxis. We have now tested the effectiveness of this mechanism using a computational model of cell movement and chemotaxis based on pseudopod autocatalysis. The model reproduces a surprisingly wide range of existing data about cell movement and chemotaxis. It simulates cell polarization and persistence without stimuli and selection of accurate pseudopods when chemoattractant gradients are present. It predicts both bias of pseudopod position in low chemoattractant gradients and--unexpectedly--lateral pseudopod initiation in high gradients. To test the predictive ability of the model, we looked for untested and novel predictions. One prediction from the model is that the angle between successive pseudopods at the front of the cell will increase in proportion to the difference between the cell's direction and the direction of the gradient. We measured the angles between pseudopods in chemotaxing Dictyostelium cells under different conditions and found the results agreed with the model extremely well. Our model and data together suggest that in rapidly moving cells like Dictyostelium and neutrophils an intrinsic pseudopod cycle lies at the heart of cell motility. This implies that the mechanism behind chemotaxis relies on modification of intrinsic pseudopod behaviour, more than generation of new pseudopods or actin polymerization by chemoattractants.

Associations between Seattle Heart Failure Model scores and health utilities: findings from HF-ACTION.

BACKGROUND: The Seattle Heart Failure Model (SHFM) is a well validated prediction model of all-cause mortality in patients with heart failure, but its relationship with generic health status measures has not been evaluated. We sought to investigate relationships between SHFM scores and health utility weights, which are necessary to estimate quality-adjusted life-years in cost-effectiveness analyses. METHODS AND RESULTS: We applied mixed linear regression to examine relationships between baseline SHFM scores and EQ-5D-derived health utilities collected longitudinally in a large clinical trial. A 1-unit increase in SHFM score (higher predicted mortality) was associated with a 0.030 decrease in utility (P < .001) and an additional 0.006 decrease per year (P < .001). With SHFM score modeled as a categorical variable, EQ-5D utilities for patients with rounded SHFM scores of 1 or 2 were significantly lower (-0.041 and -0.053, respectively; both P < .001) and declined more rapidly over time (-0.011 and -0.020, respectively; both P ≤ .004) than for patients with scores of -1. CONCLUSIONS: Patients with higher SHFM-predicted mortality had significantly lower health utilities at baseline and greater rates of decline over time, compared with patients with lower SHFM-predicted mortality. These relationships can be applied when examining the cost-effectiveness of heart failure interventions.

Fam49/CYRI interacts with Rac1 and locally suppresses protrusions.

Actin-based protrusions are reinforced through positive feedback, but it is unclear what restricts their size, or limits positive signals when they retract or split. We identify an evolutionarily conserved regulator of actin-based protrusion: CYRI (CYFIP-related Rac interactor) also known as Fam49 (family of unknown function 49). CYRI binds activated Rac1 via a domain of unknown function (DUF1394) shared with CYFIP, defining DUF1394 as a Rac1-binding module. CYRI-depleted cells have broad lamellipodia enriched in Scar/WAVE, but reduced protrusion-retraction dynamics. Pseudopods induced by optogenetic Rac1 activation in CYRI-depleted cells are larger and longer lived. Conversely, CYRI overexpression suppresses recruitment of active Scar/WAVE to the cell edge, resulting in short-lived, unproductive protrusions. CYRI thus focuses protrusion signals and regulates pseudopod complexity by inhibiting Scar/WAVE-induced actin polymerization. It thus behaves like a 'local inhibitor' as predicted in widely accepted mathematical models, but not previously identified in cells. CYRI therefore regulates chemotaxis, cell migration and epithelial polarization by controlling the polarity and plasticity of protrusions.

Use of the parameterised finite element method to robustly and efficiently evolve the edge of a moving cell.

In this paper we present a computational tool that enables the simulation of mathematical models of cell migration and chemotaxis on an evolving cell membrane. Recent models require the numerical solution of systems of reaction-diffusion equations on the evolving cell membrane and then the solution state is used to drive the evolution of the cell edge. Previous work involved moving the cell edge using a level set method (LSM). However, the LSM is computationally very expensive, which severely limits the practical usefulness of the algorithm. To address this issue, we have employed the parameterised finite element method (PFEM) as an alternative method for evolving a cell boundary. We show that the PFEM is far more efficient and robust than the LSM. We therefore suggest that the PFEM potentially has an essential role to play in computational modelling efforts towards the understanding of many of the complex issues related to chemotaxis.