circular variance analysis pipeline Search Results


circular variance analysis pipeline  (MathWorks Inc)
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MathWorks Inc circular variance analysis pipeline
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) <t>Circular</t> <t>variance</t> of actin cytoskeleton fibers for pre-senescent and senescent lung fibroblasts (n ≥ 25, N = 3). (c) <t>Analysis</t> 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.
Circular Variance Analysis Pipeline, supplied by MathWorks Inc, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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circular variance analysis pipeline - by Bioz Stars, 2026-03
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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.

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

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.

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