Browsing by Author "Liang, J"

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    Inhibition of pulmonary fibrosis in mice by CXCL10 requires glycosaminoglycan binding and syndecan-4.
    (J Clin Invest, 2010-06) Jiang, D; Liang, J; Campanella, GS; Guo, R; Yu, S; Xie, T; Liu, N; Jung, Y; Homer, R; Meltzer, EB; Li, Y; Tager, AM; Goetinck, PF; Luster, AD; Noble, PW
    Pulmonary fibrosis is a progressive, dysregulated response to injury culminating in compromised lung function due to excess extracellular matrix production. The heparan sulfate proteoglycan syndecan-4 is important in mediating fibroblast-matrix interactions, but its role in pulmonary fibrosis has not been explored. To investigate this issue, we used intratracheal instillation of bleomycin as a model of acute lung injury and fibrosis. We found that bleomycin treatment increased syndecan-4 expression. Moreover, we observed a marked decrease in neutrophil recruitment and an increase in both myofibroblast recruitment and interstitial fibrosis in bleomycin-treated syndecan-4-null (Sdc4-/-) mice. Subsequently, we identified a direct interaction between CXCL10, an antifibrotic chemokine, and syndecan-4 that inhibited primary lung fibroblast migration during fibrosis; mutation of the heparin-binding domain, but not the CXCR3 domain, of CXCL10 diminished this effect. Similarly, migration of fibroblasts from patients with pulmonary fibrosis was inhibited in the presence of CXCL10 protein defective in CXCR3 binding. Furthermore, administration of recombinant CXCL10 protein inhibited fibrosis in WT mice, but not in Sdc4-/- mice. Collectively, these data suggest that the direct interaction of syndecan-4 and CXCL10 in the lung interstitial compartment serves to inhibit fibroblast recruitment and subsequent fibrosis. Thus, administration of CXCL10 protein defective in CXCR3 binding may represent a novel therapy for pulmonary fibrosis.
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    Using Model Analysis to Unveil Hidden Patterns in Tropical Forest Structures
    (Frontiers in Ecology and Evolution, 2021-11-30) Picard, N; Mortier, F; Ploton, P; Liang, J; Derroire, G; Bastin, JF; Ayyappan, N; Bénédet, F; Boyemba Bosela, F; Clark, CJ; Crowther, TW; Engone Obiang, NL; Forni, É; Harris, D; Ngomanda, A; Poulsen, JR; Sonké, B; Couteron, P; Gourlet-Fleury, S
    When ordinating plots of tropical rain forests using stand-level structural attributes such as biomass, basal area and the number of trees in different size classes, two patterns often emerge: a gradient from poorly to highly stocked plots and high positive correlations between biomass, basal area and the number of large trees. These patterns are inherited from the demographics (growth, mortality and recruitment) and size allometry of trees and tend to obscure other patterns, such as site differences among plots, that would be more informative for inferring ecological processes. Using data from 133 rain forest plots at nine sites for which site differences are known, we aimed to filter out these patterns in forest structural attributes to unveil a hidden pattern. Using a null model framework, we generated the anticipated pattern inherited from individual allometric patterns. We then evaluated deviations between the data (observations) and predictions of the null model. Ordination of the deviations revealed site differences that were not evident in the ordination of observations. These sites differences could be related to different histories of large-scale forest disturbance. By filtering out patterns inherited from individuals, our model analysis provides more information on ecological processes.