NF-κB drives epithelial-mesenchymal mechanisms of lung fibrosis in a translational lung cell model.

In the progression phase of idiopathic pulmonary fibrosis (IPF), the normal alveolar structure of the lung is lost and replaced by remodeled fibrotic tissue and by bronchiolized cystic airspaces. Although these are characteristic features of IPF, knowledge of specific interactions between these pathological processes is limited. Here, the interaction of lung epithelial and lung mesenchymal cells was investigated in a coculture model of human primary airway epithelial cells (EC) and lung fibroblasts (FB). Single-cell RNA sequencing revealed that the starting EC population was heterogenous and enriched for cells with a basal cell signature. Furthermore, fractions of the initial EC and FB populations adopted distinct pro-fibrotic cell differentiation states upon cocultivation, resembling specific cell populations that were previously identified in lungs of patients with IPF. Transcriptomic analysis revealed active NF-κB signaling early in the cocultured EC and FB, and the identified NF-κB expression signatures were found in "HAS1 High FB" and "PLIN2+ FB" populations from IPF patient lungs. Pharmacological blockade of NF-κB signaling attenuated specific phenotypic changes of EC and prevented FB-mediated interleukin-6, interleukin-8, and CXC chemokine ligand 6 cytokine secretion, as well as collagen α-1(I) chain and α-smooth muscle actin accumulation. Thus, we identified NF-κB as a potential mediator, linking epithelial pathobiology with fibrogenesis.

GPCR-induced YAP activation sensitizes fibroblasts to profibrotic activity of TGFß1.

Tissue fibrosis is a pathological condition characterized by uncontrolled fibroblast activation that ultimately leads to organ failure. The TGFß1 pathway, one of the major players in establishment of the disease phenotype, is dependent on the transcriptional co-activators YAP/TAZ. We were interested whether fibroblasts can be sensitized to TGFß1 by activation of the GPCR/YAP/TAZ axis and whether this mechanism explains the profibrotic properties of diverse GPCR ligands. We found that LPA, S1P and thrombin cooperate in human dermal fibroblasts with TGFß1 to induce extracellular matrix synthesis, myofibroblast marker expression and cytokine secretion. Whole genome expression profiling identified a YAP/TAZ signature behind the synergistic profibrotic effects of LPA and TGFß1. LPA, S1P and thrombin stimulation led to activation of the Rho-YAP axis, an increase of nuclear YAP-Smad2 complexes and enhanced expression of profibrotic YAP/Smad2-target genes. More generally, dermal, cardiac and lung fibroblast responses to TGFß1 could be enhanced by increasing YAP nuclear levels (with GPCR ligands LPA, S1P, thrombin or Rho activator) and inhibited by decreasing nuclear YAP (with Rho inhibitor, forskolin, latrunculin B or 2-deoxy-glucose). Thus, we present here a conceptually interesting finding that fibroblast responses to TGFß1 can be predicted based on the nuclear levels of YAP and modulated by stimuli/treatments that change YAP nuclear levels. Our study contributes to better understanding of fibrosis as a complex interplay of signalling pathways and proposes YAP/TAZ as promising targets in the treatment of fibrosis.

S1P1 Modulator-Induced G αi Signaling and ß-Arrestin Recruitment Are Both Necessary to Induce Rapid and Efficient Reduction of Blood Lymphocyte Count In Vivo.

S1P1 (sphingosine-1-phosphate receptor 1) agonists prevent lymphocyte egress from secondary lymphoid organs and cause a reduction in the number of circulating blood lymphocytes. We hypothesized that S1P1 receptor modulators with pathway-selective signaling properties could help to further elucidate the molecular mechanisms involved in lymphocyte trapping. A proprietary S1P1 receptor modulator library was screened for compounds with clear potency differences in ß-arrestin recruitment and G protein alpha i subunit (G αi) protein-mediated signaling. We describe here the structure-activity relationships of highly potent S1P1 modulators with apparent pathway selectivity for ß-arrestin recruitment. The most differentiated compound, D3-2, displayed a 180-fold higher potency in the ß-arrestin recruitment assay (EC50 0.9 nM) compared with the G αi-activation assay (167 nM), whereas ponesimod, a S1P1 modulator that is currently in advanced clinical development in multiple sclerosis, was equipotent in both assays (EC50 1.5 and 1.1 nM, respectively). Using these novel compounds as pharmacological tools, we showed that although a high potency in ß-arrestin recruitment is required to fully internalize S1P1 receptors, the potency in inducing G αi signaling determines the rate of receptor internalization in vitro. In contrast to ponesimod, the compound D3-2 did not reduce the number or circulating lymphocytes in rats despite high plasma exposures. Thus, for rapid and maximal S1P1 receptor internalization a high potency in both G αi signaling and ß-arrestin recruitment is mandatory and this translates into efficient reduction of the number of circulating lymphocytes in vivo.

Impact of scale space search on age- and gender-related changes in MRI-based cortical morphometry.

In magnetic resonance imaging based brain morphometry, Gaussian smoothing is often applied to increase the signal-to-noise ratio and to increase the detection power of statistical parametric maps. However, most existing studies used a single smoothing filter without adequately justifying their choices. In this article, we want to determine the extent for which performing a morphometry analysis using multiple smoothing filters, namely conducting a scale space search, improves or decreases the detection power. We first compared scale space search with single-filter analysis through a simulated population study. The multiple comparisons in our four-dimensional scale space searches were corrected for using a unified P-value approach. Our results illustrate that, compared with a single-filter analysis, a scale space search analysis can properly capture the variations in analysis results caused by variations in smoothing, and more importantly, it can obviously increase the sensitivity for detecting brain morphometric changes. We also show that the cost of an increased critical threshold for conducting a scale space search is very small. In the second experiment, we investigated age and gender effects on cortical volume, thickness, and surface area in 104 normal subjects using scale space search. The obtained results provide a perspective of scale space theory on the morphological changes with age and gender. These results suggest that, in exploratory studies of aging, gender, and disease, conducting a scale space search is essential, if we are to produce a complete description of the structural changes or abnormalities associated with these dimensions.

Anisotropic diffusion of tensor fields for fold shape analysis on surfaces.

The folding pattern of the human cortical surface is organized in a coherent set of troughs and ridges, which mark important anatomical demarcations that are similar across subjects. Cortical surface shape is often analyzed in the literature using isotropic diffusion, a strategy that is questionable because many anatomical regions are known to follow the direction of folds. This paper introduces anisotropic diffusion kernels to follow neighboring fold directions on surfaces, extending recent literature on enhancing curve-like patterns in images. A second contribution is to map deformations that affect sulcal length, i.e., are parallel to neighboring folds, with other deformations that affect sulcal length, within the diffusion process. Using the proposed method, we demonstrate anisotropic shape differences of the cortical surface associated with aging in a database of 95 healthy subjects, such as a contraction of the cingulate sulcus, shorter gyri in the temporal lobe and a contraction in the frontal lobe.

Oriented morphometry of folds on surfaces.

The exterior surface of the brain is characterized by a juxtaposition of crests and troughs that together form a folding pattern. The majority of the deformations that occur in the normal course of adult human development result in folds changing their length or width. Current statistical shape analysis methods cannot easily discriminate between these two cases. Using discrete exterior calculus and Tikhonov regularization, we develop a method to estimate a dense orientation fiel in the tangent space of a surface described by a triangulated mesh, in the direction of its folds. We then use this orientation field to distinguish between shape differences in the direction parallel to folds and those in the direction across them. We test the method quantitatively on synthetic data and qualitatively on a database consisting of segmented cortical surfaces of 92 healthy subjects and 97 subjects with Alzheimer's disease. The method estimates the correct fold directions and also indicates that the healthy and diseased subjects are distinguished by shape differences that are in the direction perpendicular to the underlying hippocampi, a finding which is consistent with the neuroscientific literature. These results demonstrate the importance of direction specific computational methods for shape analysis.

Depth potential function for folding pattern representation, registration and analysis.

Some surfaces present folding patterns formed by juxtapositions of ridges and valleys as, for example, the cortical surface of the human brain. The fundamental problem with ridges is to find a correspondence among and analyze the variability among them. Many techniques to achieve these goals exist but use scalar functions. Depth maps are used to efficiently project the geometry of folds into a scalar function in the case where a natural projection plane exists. However, in most cases of curved surfaces, there is no natural projection plane to represent folding patterns. This paper studies the problem of shape matching and analysis of folding patterns by extending the notion of depth maps when no natural projection plane exists. The novel depth measure is called a depth potential function. The depth potential function integrates the information known from the curvature of the surface into a point-of-view invariant representation. The main advantage of the depth potential function is that it is computed by solving a time independent Poisson equation. The Poisson equation endows our surface representation with a significant computational advantage that makes it orders of magnitude faster to compute compared with other available surface representations. The method described in this paper was validated using both synthetic surfaces and cortical surfaces of human brain acquired by magnetic resonance imaging. On average, the improvement in shape matching when using the depth potential was of 11%, which is considerable.

An unbiased iterative group registration template for cortical surface analysis.

Accurate alignment of explicit surface representations of human cerebral cortices is necessary in order to compare local individual differences in cortical morphometric measurements (thickness, surface area, gyrification, etc.) in both normal and clinical populations. This paper presents a methodology for developing unbiased, high resolution iterative registration templates from a group of 222 subject hemispheres and shows that the resulting template provides better alignment of a separate set of test data than single-subject templates. It demonstrates that between 30 and 50 subjects are required to generate a stable iterative template. It also explores the way in which fold variants in registration templates affect the quality of registration. Finally, it shows that hemisphere-specific group registration templates systematically better register subject hemispheres of the same laterality, underlining the need to develop templates free of hemisphere bias for asymmetry analysis.