Journal: APL Bioengineering

Article Title: Fibroblast senescence-associated extracellular matrix promotes heterogeneous lung niche

doi: 10.1063/5.0204393

Figure Lengend Snippet: Senescent fibroblasts have disorganized actin cytoskeleton and upregulated integrin profile. (a) Representative confocal microscopy images of pre-senescent and senescent fibroblasts stained with Hoechst 33342 and phalloidin rhodamine (obj. = 60×, N.A. = 1.3, scale bar = 20 μ m). (b) Circular variance of actin cytoskeleton fibers for pre-senescent and senescent lung fibroblasts (n ≥ 25, N = 3). (c) Analysis of CD29, CD61, CD51, and CD49b integrin profile for pre-senescent and senescent lung fibroblasts (n ≥ 500,000 cells per condition, N = 3). (d) Schematic of proposed method of SA-ECM matrix disorganization by senescent lung fibroblasts (Created with BioRender.com ). Mean ± SEM; T-Test, * P ≤ 0.05, ** P ≤ 0.01, *** P ≤ 0.001, **** P ≤ 0.0001.

Article Snippet: For the analysis of histology, no adjustments were made to the MATLAB circular variance analysis pipeline.

Techniques: Confocal Microscopy, Staining

Journal: APL Bioengineering

Article Title: Fibroblast senescence-associated extracellular matrix promotes heterogeneous lung niche

doi: 10.1063/5.0204393

Figure Lengend Snippet: Regional matrix analysis of human interstitial pulmonary fibrosis tissue samples. (a) Representative image of Masson's trichrome stained interstitial (obj. = 40×, N.A. = 0.95, large image scale bar = 200 μ m, zoom scale bar = 50 μ m). (b) Simple linear regression of global circular variance vs age of pulmonary fibrosis patient (n = 2 samples per patient, N = 23 patients). (c) Simple linear regression of anisotropic circular variance vs age of pulmonary fibrosis patient (n = 2 samples per patient, N = 23 patients). (d) Representative image of p16-stained pulmonary fibrosis patient tissue sample (obj. = 40×, N.A. = 0.95, large image scale bar = 200 μ m, zoom scale bar = 20 μ m). (e) Simple linear regression of percent of p16-positive cells vs age of pulmonary fibrosis patient (n = 2 samples per patient, N = 23 patients). (f) Simple linear regression of percent of p16-positive cells vs global circular variance of pulmonary fibrosis patient (n = 2 samples per patient, N = 23 patients). (g) Simple linear regression of percent of p16-positive cells vs anisotropic circular variance of pulmonary fibrosis patient (n = 2 samples per patient, N = 23 patients). Simple linear regression. * P ≤ 0.05, ** P ≤ 0.01, *** P ≤ 0.001, **** P ≤ 0.0001.

Article Snippet: For the analysis of histology, no adjustments were made to the MATLAB circular variance analysis pipeline.

Techniques: Staining

Journal: Nature Communications

Article Title: A browser-based tool for visualization and analysis of diffusion MRI data

doi: 10.1038/s41467-018-03297-7

Figure Lengend Snippet: Development of the corticospinal tract, arcuate fasciculus, and cingulum. Tract profiles of mean diffusivity (top) and fractional anisotropy (bottom) are shown for the left hemisphere corticospinal tract (CST, orange), arcuate fasciculus (blue), and cingulum (green). Splitting the group by age, and selecting 3 bins, displays mean lines of three groups: 8–15 (red), 15–30 (purple), and 30–50 (blue). For the CST, there is a region that shows a decrease in FA with development, and this location of the tract is highlighted on the plot using the “brushable tracts” feature (shaded gray box). The linked view in the anatomy displays the portion of the CST that is brushed in the plot demonstrating that this effect occurs in the anatomical portion of the CST known as the centrum semiovale, adjacent to the arcuate fasciculus. This linked visualization provides a connection between the data plots and the 3D Anatomy. Data and MATLAB code are available at https://github.com/YeatmanLab/AFQ-Browser_data (see Figure2_Development.m) and running AFQ-Browser instance at: https://YeatmanLab.github.io/AFQBrowser-demo/ )

Article Snippet: AFQ-Browser takes the output of the AFQ MATLAB tractometry pipeline, and generates a browser-based visualization of the results.

Techniques: