Blood CD9+ B cell, a biomarker of bronchiolitis obliterans syndrome after lung transplantation

Bronchiolitis obliterans syndrome is the main limitation for long-term survival after lung transplantation. Some specific B cell populations are associated with long-term graft acceptance. We aimed to monitor the B cell profile during early development of bronchiolitis obliterans syndrome after lung transplantation. The B cell longitudinal profile was analyzed in peripheral blood mononuclear cells from patients with bronchiolitis obliterans syndrome and patients who remained stable over 3 years of follow-up. CD24^hi CD38^hi transitional B cells were increased in stable patients only, and reached a peak 24 months after transplantation, whereas they remained unchanged in patients who developed a bronchiolitis obliterans syndrome. These CD24^hi CD38^hi transitional B cells specifically secrete IL-10 and express CD9. Thus, patients with a total CD9⁺ B cell frequency below 6.6% displayed significantly higher incidence of bronchiolitis obliterans syndrome (AUC = 0.836, PPV = 0.75, NPV = 1). These data are the first to associate IL-10-secreting CD24^hi CD38^hi transitional B cells expressing CD9 with better allograft outcome in lung transplant recipients. CD9-expressing B cells appear as a contributor to a favorable environment essential for the maintenance of long-term stable graft function and as a new predictive biomarker of bronchiolitis obliterans syndrome-free survival.

[Indications of lung transplantation: Patients selection, timing of listing, and choice of procedure]

Lung transplantation (LT) is now considered as an excellent treatment option for selected patients with end-stage pulmonary diseases, such as COPD, cystic fibrosis, idiopathic pulmonary fibrosis, and pulmonary arterial hypertension. The 2 goals of LT are to provide a survival benefit and to improve quality of life. The 3-step decision process leading to LT is discussed in this review. The first step is the selection of candidates, which requires a careful examination in order to check absolute and relative contraindications. The second step is the timing of listing for LT; it requires the knowledge of disease-specific prognostic factors available in international guidelines, and discussed in this paper. The third step is the choice of procedure: indications of heart-lung, single-lung, and bilateral-lung transplantation are described. In conclusion, this document provides guidelines to help pulmonologists in the referral and selection processes of candidates for transplantation in order to optimize the outcome of LT.

[Does antifungal therapy influence postoperative morbidity or long-term survival after surgical resection for pulmonary aspergilloma?]

BACKGROUND

Surgical resection of pulmonary aspergilloma is associated with symptoms control, complications prevention, and improved survival, given that the disease is localized and the patient fit enough to undergo surgery. In these operable forms, the impact of perioperative antifungal therapy remains controversial. The purpose of this study was to analyze the impact of antifungal therapy on postoperative morbidity and overall survival in patients with operable pulmonary aspergilloma.

METHODS

The clinical records of 113 patients who underwent thoracic surgery for aspergilloma in our institution from January 1989 to December 2010 were retrospectively reviewed. Of these, 64 patients received antifungal therapy in the perioperative period and were included in group 1, and 49 patients did not receive antifungal therapy and were included in group 2.

RESULTS

Postoperative complication rates were 31.2% in group 1 and 20.4% in group 2 (P = 0.30). Univariable analysis showed that immunocompromised status (P < 0.001), past history of cancer (P = 0.50), preoperative purulent sputum (P = 0.024), and pneumonectomy (P < 0.001) were significantly associated with postoperative complications, but that antifungal therapy was not. Five- and 10-year overall survival rates were respectively 78.3% and 57.8% in group 1 vs. 85.9% and 65.7% in group 2 (P = 0.23). Multivariate analysis revealed that age higher than 50, immunocompromised status and pneumonectomy were significantly associated with adverse long-term survival (χ(2) = 6.59, df = 5, P < 0.001), but that antifungal therapy was not.

CONCLUSION

Antifungal therapy has no significant impact on postoperative morbidity or long-term survival following surgical resection of pulmonary aspergilloma. Such procedure is associated with acceptable postoperative morbidity and long-term survival.

Steady-state fluctuations of a genetic feedback loop: an exact solution

Genetic feedback loops in cells break detailed balance and involve bimolecular reactions; hence, exact solutions revealing the nature of the stochastic fluctuations in these loops are lacking. We here consider the master equation for a gene regulatory feedback loop: a gene produces protein which then binds to the promoter of the same gene and regulates its expression. The protein degrades in its free and bound forms. This network breaks detailed balance and involves a single bimolecular reaction step. We provide an exact solution of the steady-state master equation for arbitrary values of the parameters, and present simplified solutions for a number of special cases. The full parametric dependence of the analytical non-equilibrium steady-state probability distribution is verified by direct numerical solution of the master equations. For the case where the degradation rate of bound and free protein is the same, our solution is at variance with a previous claim of an exact solution [J. E. M. Hornos, D. Schultz, G. C. P. Innocentini, J. Wang, A. M. Walczak, J. N. Onuchic, and P. G. Wolynes, Phys. Rev. E 72, 051907 (2005), and subsequent studies]. We show explicitly that this is due to an unphysical formulation of the underlying master equation in those studies.

[Lung volume reduction surgery for emphysema and bullous pulmonary emphysema]

The improvement of respiratory symptoms for emphysematous patients by surgery is a concept that has evolved over time. Initially used for giant bullae, this surgery was then applied to patients with diffuse microbullous emphysema. The physiological and pathological concepts underlying these surgical procedures are the same in both cases: improve respiratory performance by reducing the high intrapleural pressure. The functional benefit of lung volume reduction surgery (LVRS) in the severe diffuse emphysema has been validated by the National Emphysema Treatment Trial (NETT) and the later studies which allowed to identify prognostic factors. The quality of the clinical, morphological and functional data made it possible to develop recommendations now widely used in current practice. Surgery for giant bullae occurring on little or moderately emphysematous lung is often a simpler approach but also requires specialised support to optimize its results.

An effective rate equation approach to reaction kinetics in small volumes: theory and application to biochemical reactions in nonequilibrium steady-state conditions

Chemical master equations provide a mathematical description of stochastic reaction kinetics in well-mixed conditions. They are a valid description over length scales that are larger than the reactive mean free path and thus describe kinetics in compartments of mesoscopic and macroscopic dimensions. The trajectories of the stochastic chemical processes described by the master equation can be ensemble-averaged to obtain the average number density of chemical species, i.e., the true concentration, at any spatial scale of interest. For macroscopic volumes, the true concentration is very well approximated by the solution of the corresponding deterministic and macroscopic rate equations, i.e., the macroscopic concentration. However, this equivalence breaks down for mesoscopic volumes. These deviations are particularly significant for open systems and cannot be calculated via the Fokker-Planck or linear-noise approximations of the master equation. We utilize the system-size expansion including terms of the order of Omega(-1/2) to derive a set of differential equations whose solution approximates the true concentration as given by the master equation. These equations are valid in any open or closed chemical reaction network and at both the mesoscopic and macroscopic scales. In the limit of large volumes, the effective mesoscopic rate equations become precisely equal to the conventional macroscopic rate equations. We compare the three formalisms of effective mesoscopic rate equations, conventional rate equations, and chemical master equations by applying them to several biochemical reaction systems (homodimeric and heterodimeric protein-protein interactions, series of sequential enzyme reactions, and positive feedback loops) in nonequilibrium steady-state conditions. In all cases, we find that the effective mesoscopic rate equations can predict very well the true concentration of a chemical species. This provides a useful method by which one can quickly determine the regions of parameter space in which there are maximum differences between the solutions of the master equation and the corresponding rate equations. We show that these differences depend sensitively on the Fano factors and on the inherent structure and topology of the chemical network. The theory of effective mesoscopic rate equations generalizes the conventional rate equations of physical chemistry to describe kinetics in systems of mesoscopic size such as biological cells.

Crowding-induced anisotropic transport modulates reaction kinetics in nanoscale porous media

We quantify the emergence of persistent anisotropy in the diffusion of spherical tracer particles through a nanoscale porous medium composed of a uniform distribution of purely symmetric crowding particles. We focus on the interior of a biological cell as an example of such a medium and find that diffusion is highly directional for distances comparable to the size of some organelles. We use a geometrical procedure that avoids the standard orientational averaging to quantify the anisotropy of diffusive paths and show that the point source distributions are predominantly of prolate ellipsoidal shape as a result of local volume exclusion. This geometrical symmetry breaking strongly skews the distribution of kinetic rates of diffusion-limited reactions toward small values, leading to the result that, for short to intermediate times, almost 80% of the rates measured in an ensemble of heterogeneous media are smaller than the expected rate in an ideal homogeneous medium of similar excluded volume fraction. This crowding-induced modulation may have implications for our understanding and measurement of diffusion-controlled intracellular reaction kinetics and for experimental nanotechnology applications, such as nanoparticle-based bioimaging and drug delivery, where diffusion plays an important role.

Noise-induced breakdown of the Michaelis-Menten equation in steady-state conditions

The Michaelis-Menten (MM) equation is the basic equation of enzyme kinetics; it is also a basic building block of many models of biological systems. We build a stochastic and microscopic model of enzyme kinetics inside a small subcellular compartment. Using both theory and simulations, we show that intrinsic noise induces a breakdown of the MM equation even if steady-state metabolic conditions are enforced. In particular, we show that (i) given a reaction velocity, deterministic rate equations can severely underestimate steady-state intracellular substrate concentrations and (ii) different reaction schemes which on a macroscopic level are indistinguishable because they are described by the same MM equation obey distinctly different equations in subcellular compartments.

Brownian motion of an asymmetrical particle in a potential field

It is well known that a free ellipsoidal Brownian particle exhibits anisotropic diffusion for short times which changes to isotropic at long times, and, that the long-time diffusion coefficient is an average of the translational diffusion coefficients along the different semiaxes of the particle. We show analytically that in the presence of external forces, the long-time diffusion coefficient is different from that of a free particle. The magnitude of the difference in the two diffusion coefficients is found to increase proportionately with the particle's asymmetry, being zero only for a perfectly spherical Brownian particle. It is also found that, for asymmetrical particles, the application of external forces can amplify the non-Gaussian character of the spatial probability distributions which consequently delays the transition to the classical behavior. We illustrate these phenomena by considering the quasi-two-dimensional Brownian motion of an ellipsoidal rigid particle in linear and harmonic potential fields. These two examples provide insight into the role played by particle asymmetry in electrophoresis and microconfinement due to a laser trap or due to intracellular macromolecular crowding.

A systematic investigation of the rate laws valid in intracellular environments

Recently there has been significant interest in deducing the form of the rate laws for chemical reactions occurring in the intracellular environment. This environment is typically characterized by low-dimensionality and a high macromolecular content; this leads to a spatial heterogeneity not typical of the well stirred in vitro environments. For this reason, the classical law of mass action has been presumed to be invalid for modeling intracellular reactions. Using lattice-gas automata models, it has recently been postulated [H. Berry, Monte Carlo simulations of enzyme reactions in two dimensions: Fractal kinetics and spatial segregation, Biophys. J. 83 (2002) 1891-1901; S. Schnell, T.E. Turner, Reaction kinetics in intracellular environments with macromolecular crowding: simulations and rate laws, Prog. Biophys. Mol. Biol. 85 (2004) 235-260] that the reaction kinetics is fractal-like. In this article we systematically investigate for the first time how the rate laws describing intracellular reactions vary as a function of: the geometry and size of the intracellular surface on which the reactions occur, the mobility of the macromolecules responsible for the crowding effects, the initial reactant concentrations and the probability of reaction between two reactant molecules. We also compare the rate laws valid in heterogeneous environments in which there is an underlying spatial lattice, for example crystalline alloys, with the rate laws valid in heterogeneous environments where there is no such natural lattice, for example in intracellular environments. Our simulations indicate that: (i) in intracellular environments both fractal kinetics and mass action can be valid, the major determinant being the probability of reaction, (ii) the geometry and size of the intracellular surface on which reactions are occurring does not significantly affect the rate law, (iii) there are considerable differences between the rate laws valid in heterogeneous non-living structures such as crystals and those valid in intracellular environments. Deviations from mass action are less pronounced in intracellular environments than in a crystalline material of similar heterogeneity.

Phase transitions and superuniversality in the dynamics of a self-driven particle

We study an active random walker model in which a particle's motion is determined by a self-generated field. The field encodes information about the particle's path history. This leads to either self-attractive or self-repelling behavior. For self-repelling behavior, we find a phase transition in the dynamics: when the coupling between the field and the walker exceeds a critical value, the particle's behavior changes from renormalized diffusion to one characterized by a diverging diffusion coefficient. The dynamical behavior for all cases is surprisingly independent of dimension and of the noise amplitude.

Strong-coupling dynamics of a multicellular chemotactic system

Chemical signaling is one of the ubiquitous mechanisms by which intercellular communication takes place at the microscopic level, particularly via chemotaxis. Such multicellular systems are popularly studied using continuum, mean-field equations. In this Letter we study a stochastic model of chemotactic signaling. The Langevin formalism of the model makes it amenable to calculation via nonperturbative analysis, which enables a quantification of the effect of fluctuations on both the weak and the strongly coupled biological dynamics. In particular, we show that the (i) self-localization due to autochemotaxis is impossible. (ii) When aggregation occurs, the aggregate performs a random walk with a renormalized diffusion coefficient D(R) proportiuonal to epsilon-2N-3. (iii) The stochastic model exhibits sharp transitions in cell motile behavior for negative chemotaxis, behavior that has no parallel in the mean-field Keller-Segel equations.

Many-body theory of chemotactic cell-cell interactions

We consider an individual-based stochastic model of cell movement mediated by chemical signaling fields. This model is formulated using Langevin dynamics, which allows an analytic study using methods from statistical and many-body physics. In particular we construct a diagrammatic framework within which to study cell-cell interactions. In the mean-field limit, where statistical correlations between cells are neglected, we recover the deterministic Keller-Segel equations. Within exact perturbation theory in the chemotactic coupling epsilon , statistical correlations are non-negligible at large times and lead to a renormalization of the cell diffusion coefficient D(R)--an effect that is absent at mean-field level. An alternative closure scheme, based on the necklace approximation, probes the strong coupling behavior of the system and predicts that D(R) is renormalized to zero at a critical value of epsilon, indicating self-localization of the cell. Stochastic simulations of the model give very satisfactory agreement with the perturbative result. At higher values of the coupling simulations indicate that D(R) approximately epsilon(-2) , a result at odds with the necklace approximation. We briefly discuss an extension of our model, which incorporates the effects of short-range interactions such as cell-cell adhesion.

Accurate discretization of advection-diffusion equations

We present an exact mathematical transformation which converts a wide class of advection-diffusion equations into a form allowing simple and direct spatial discretization in all dimensions, and thus the construction of accurate and more efficient numerical algorithms. These discretized forms can also be viewed as master equations which provide an alternative mesoscopic interpretation of advection-diffusion processes in terms of diffusion with spatially varying hopping rates.