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21 pages, 3287 KiB  
Article
Stage-Dependent Fibrotic Gene Profiling of WISP1-Mediated Fibrogenesis in Human Fibroblasts
by Kirti Singh, Marta Witek, Jaladhi Brahmbhatt, Jacquelyn McEntire, Kannan Thirunavukkarasu and Sunday S. Oladipupo
Cells 2024, 13(23), 2005; https://doi.org/10.3390/cells13232005 - 5 Dec 2024
Viewed by 1189
Abstract
Idiopathic pulmonary fibrosis (IPF) is the most common interstitial lung disease with unknown etiology, characterized by chronic inflammation and tissue scarring. Although, Pirfenidone and Nintedanib slow the disease progression, no currently available drugs or therapeutic interventions address the underlying cause, highlighting the unmet [...] Read more.
Idiopathic pulmonary fibrosis (IPF) is the most common interstitial lung disease with unknown etiology, characterized by chronic inflammation and tissue scarring. Although, Pirfenidone and Nintedanib slow the disease progression, no currently available drugs or therapeutic interventions address the underlying cause, highlighting the unmet medical need. A matricellular protein, Wnt-1-induced secreted protein 1 (WISP1), also referred to as CCN4 (cellular communication network factor 4), is a secreted multi-modular protein implicated in multi-organ fibrosis. Although the precise mechanism of WISP1-mediated fibrosis remains unclear, emerging evidence indicates that WISP1 is profibrotic in nature. While WISP1-targeting therapy is applied in the clinic for fibrosis, detailed interrogation of WISP1-mediated fibrogenic molecular and biological pathways is lacking. Here, for the first time, using NanoString® technology, we identified a novel WISP1-associated profibrotic gene signature and molecular pathways potentially involved in the initiation and progression of fibrosis in primary human dermal and lung fibroblasts from both healthy individuals and IPF patients. Our data demonstrate that WISP1 is upregulated in IPF-lung fibroblasts as compared to healthy control. Furthermore, our results confirm that WISP1 is downstream of the transforming growth factor-β (TGFβ), and it induces fibroblast cell proliferation. Additionally, WISP1 induced IL6 and CCL2 in fibroblasts. We also developed a novel, combined TGFβ and WISP1 in vitro system to demonstrate a role for WISP1 in the progression of fibrosis. Overall, our findings uncover not only similarities but also striking differences in the molecular profile of WISP1 in human fibroblasts, both during the initiation and progression phases, as well as in disease-specific context. Full article
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Graphical abstract

Graphical abstract
Full article ">Figure 1
<p>WISP1 is endogenously upregulated in primary human DHLF. WISP1 transcript and secreted protein are expressed in NHLF and DHLF. DHLF exhibit significantly higher (<b>A</b>) WISP1 mRNA transcript and (<b>B</b>) secreted WISP1 protein in the condition media, detected by RT-qPCR and ELISA, respectively. Each data point represents one donor-derived primary cell line for both NHLF (<span class="html-italic">n</span> = 5 donors) and DHLF (<span class="html-italic">n</span> = 5 donors), with each experiment performed in triplicates and represented as mean ± SD. Statistical analysis was performed using paired <span class="html-italic">t</span>-test and significance denoted as * <span class="html-italic">p</span> &lt; 0.5 or ** <span class="html-italic">p</span> &lt; 0.01 versus healthy NHLF, as shown.</p>
Full article ">Figure 2
<p>TGFβ induces WISP1 expression in primary lung and dermal fibroblasts. Stimulation with TGFβ (1 ng/mL) for 24 h significantly increases COL1A1, COL3A1, IL6, ACTA2, FN1, and WISP1 mRNA as compared to control in (<b>A</b>) NHLF, (<b>B</b>) DHLF, and (<b>C</b>) NHDF for 3 respective donors (<span class="html-italic">n</span> = 3/each) analyzed by RT-qPCR. Notably, TGFβ decreased CCL2 in NHLF and DHLF, except in NHDF. Each experiment was independently performed in triplicates with three biological replicates (<span class="html-italic">n</span> = 3) for each donor and represented as mean ± SD. Statistical analysis was performed using one-way ANOVA with Tukey’s post hoc analysis vs. vehicle control for respective donors. * denotes <span class="html-italic">p</span> &lt; 0.5, ** denotes <span class="html-italic">p</span> &lt; 0.01, *** denotes <span class="html-italic">p</span> &lt; 0.001, **** denotes <span class="html-italic">p</span> &lt; 0.0001 versus the unstimulated control, as shown.</p>
Full article ">Figure 3
<p>WISP1 promotes a striking increase in primary human dermal fibroblast cell proliferation. (<b>A</b>) Treatment with WISP1 (1000 nM) shows a striking increase in cell proliferation (<span class="html-italic">p</span> &lt; 0.0001 via one-way ANOVA with Tukey’s post hoc analysis) detected by increased pRb positive cells as compared to control in NHDF. Representative 10× images were captured with the top image representing Hoechst nuclear stain, while the bottom panel represents pRb green fluorescence. PDGF-BB (100 nM) was used as an internal positive control to ensure assay reliability. The PDGF-BB dose response curve is shown in the <a href="#app1-cells-13-02005" class="html-app">Supplementary Materials</a>. (<b>B</b>) % pRb positive cells were calculated by dividing pRb positive cells over total number of cells calculated by nuclear Hoechst staining. Three independent experiments (<span class="html-italic">n</span> = 3) were performed in triplicates and represented as mean ± SD. Statistical analysis was performed using one-way ANOVA with Tukey’s post hoc analysis versus the vehicle-control condition and significance denoted as * <span class="html-italic">p</span> &lt; 0.5, **** <span class="html-italic">p</span> &lt; 0.0001.</p>
Full article ">Figure 4
<p>WISP1 increases CCL2 and IL6 in primary fibroblasts. Stimulation with WISP1 (1000 nM) for 24 h significantly increases CCL2 and IL6 gene expression in (<b>A</b>) NHLF, (<b>B</b>) DHLF, and (<b>C</b>) NHDF as compared to control. TGFβ (1 ng/mL) for 24 h served as a positive control and significantly increases COL1A1, COL3A1, IL6, ACTA2, FN1, and WISP1 versus vehicle control. (<b>D</b>) Stimulation with increasing WISP1 concentrations for 24 h initiates concentration-dependent increase in CCL2 and IL6 protein levels, detected via ELISA in the cell-supernatant of NHDF. Each experiment performed in duplicates with three biological replicates (<span class="html-italic">n</span> = 3) and represented as mean ± SD. Statistical analysis was performed using one-way ANOVA with Tukey’s post hoc analysis vs. vehicle control for respective donors. * denotes <span class="html-italic">p</span> &lt; 0.5, ** denotes <span class="html-italic">p</span> &lt; 0.01, *** denotes <span class="html-italic">p</span> &lt; 0.001, **** denotes <span class="html-italic">p</span> &lt; 0.0001 versus the vehicle control, as shown.</p>
Full article ">Figure 4 Cont.
<p>WISP1 increases CCL2 and IL6 in primary fibroblasts. Stimulation with WISP1 (1000 nM) for 24 h significantly increases CCL2 and IL6 gene expression in (<b>A</b>) NHLF, (<b>B</b>) DHLF, and (<b>C</b>) NHDF as compared to control. TGFβ (1 ng/mL) for 24 h served as a positive control and significantly increases COL1A1, COL3A1, IL6, ACTA2, FN1, and WISP1 versus vehicle control. (<b>D</b>) Stimulation with increasing WISP1 concentrations for 24 h initiates concentration-dependent increase in CCL2 and IL6 protein levels, detected via ELISA in the cell-supernatant of NHDF. Each experiment performed in duplicates with three biological replicates (<span class="html-italic">n</span> = 3) and represented as mean ± SD. Statistical analysis was performed using one-way ANOVA with Tukey’s post hoc analysis vs. vehicle control for respective donors. * denotes <span class="html-italic">p</span> &lt; 0.5, ** denotes <span class="html-italic">p</span> &lt; 0.01, *** denotes <span class="html-italic">p</span> &lt; 0.001, **** denotes <span class="html-italic">p</span> &lt; 0.0001 versus the vehicle control, as shown.</p>
Full article ">Figure 5
<p>Recombinant WISP1 synergistically induces inflammatory markers along with TGFβ. (<b>A</b>) Primary human fibroblasts were stimulated with TGFβ (1 ng/mL) for 24 h for initiation, followed by WISP1 (1000 nM) for another 24 h as per the experimental layout. CCL2 and IL6 mRNA expression was significantly increased in (<b>B</b>) non-diseased lung and (<b>D</b>) dermal fibroblasts, but not in (<b>C</b>) IPF-diseased lung fibroblasts. Statistical analysis was performed using one-way ANOVA with Tukey’s post hoc analysis vs. vehicle control for respective donors. * denotes <span class="html-italic">p</span> &lt; 0.5, ** denotes <span class="html-italic">p</span> &lt; 0.01, *** denotes <span class="html-italic">p</span> &lt; 0.001, **** denotes <span class="html-italic">p</span> &lt; 0.0001 versus the unstimulated control, for three biological replicates (<span class="html-italic">n</span> = 3) and represented as mean ± SD.</p>
Full article ">Figure 6
<p>WISP1 fibrotic gene signature in dermal fibroblasts. The volcano plot illustrates fibroblast genes upregulated (red) and downregulated (blue) upon stimulation with either (<b>A</b>) WISP1 alone or (<b>B</b>) in conjugation with TGFβ as compared to vehicle control (PBS) in NHDF (<span class="html-italic">n</span> = 3). The plots representing statistically significant gene with |FC| &gt; 1.5 and adj. <span class="html-italic">p</span>-value &lt; 0.1 are plotted with the x-axis representing log2 fold change (FC) versus the y-axis −log10 <span class="html-italic">p</span>-value. (<b>C</b>) The heatmap represents pathways significantly associated with the corresponding treatment condition as percent of genes influenced and the list of genes used in the pathway analysis is highlighted in <a href="#app1-cells-13-02005" class="html-app">Table S8</a>. (<b>D</b>) Scatterplot showing log2 fold change for the differentially expressed genes when comparing WISP1 + TGFβ treatment with WISP1 (x-axis) versus TGFβ (y-axis). (<b>E</b>) Venn diagram representing unique and overlapping set of genes between the WISP1, TGFβ, and WISP1 + TGFβ treatment paradigms. A comprehensive lists of genes is provided in the <a href="#app1-cells-13-02005" class="html-app">Supplementary Materials</a>.</p>
Full article ">Figure 7
<p>WISP1 fibrotic gene signature in lung fibroblasts. The volcano plot illustrates fibroblast genes upregulated (red) and downregulated (blue) upon stimulation with either (<b>A</b>) WISP1 alone or (<b>B</b>) in conjugation with TGFβ as compared to vehicle control (PBS) in NHLF (<span class="html-italic">n</span> = 3). The plots representing statistically significant gene with |FC| &gt; 1.5 and adj <span class="html-italic">p</span>-value &lt; 0.1 are plotted with the x-axis representing log2 fold change (FC) versus the y-axis −log10 <span class="html-italic">p</span>-value. (<b>C</b>) The heatmap represents pathways significantly associated with the corresponding treatment condition as percent of genes influenced and the list of genes used in the pathway analysis is highlighted in <a href="#app1-cells-13-02005" class="html-app">Table S8</a>. (<b>D</b>) Scatterplot showing log2 fold change for the differentially expressed genes when comparing WISP1 + TGFβ treatment with WISP1 (x-axis) versus TGFβ (y-axis). (<b>E</b>) Venn diagram representing unique and overlapping set of genes between the WISP1, TGFβ, and WISP1 + TGFβ treatment paradigms. A comprehensive lists of genes is provided in the <a href="#app1-cells-13-02005" class="html-app">Supplementary Materials</a>.</p>
Full article ">Figure 8
<p>WISP1 fibrotic gene signature in IPF-diseased fibroblast. The volcano plot illustrates fibroblast genes upregulated (red) and downregulated (blue) upon stimulation with either (<b>A</b>) WISP1 alone or (<b>B</b>) in conjugation with TGFβ as compared to vehicle control (PBS) in DHLF (<span class="html-italic">n</span> = 3). The plots representing statistically significant gene with |FC| &gt; 1.5 and adj <span class="html-italic">p</span>-value &lt; 0.1 are plotted with the x-axis representing log2 fold change (FC) versus the y-axis −log10 <span class="html-italic">p</span>-value. (<b>C</b>) The heatmap represents pathways significantly associated with the corresponding treatment condition as percent of genes influenced and the list of genes used in the pathway analysis is highlighted in <a href="#app1-cells-13-02005" class="html-app">Table S8</a>. (<b>D</b>) Scatterplot showing log2 fold change for the differentially expressed genes when comparing WISP1 + TGFβ treatment with WISP1 (x-axis) versus TGFβ (y-axis). (<b>E</b>) Venn diagram represents unique and overlapping set of genes between the WISP1, TGFβ, and WISP1 + TGFβ treatment paradigms. A comprehensive list of genes is provided in the <a href="#app1-cells-13-02005" class="html-app">Supplementary Materials</a>.</p>
Full article ">Figure 9
<p>Schematic summary of WISP1-TGFβ crosstalk in regulation of fibrosis progression.</p>
Full article ">
21 pages, 4475 KiB  
Article
Highly Calibrated Relationship Between Bleomycin Concentrations and Facets of the Active Phase Fibrosis in Classical Mouse Bleomycin Model
by Anil Hari Kadam and Jan E. Schnitzer
Int. J. Mol. Sci. 2024, 25(22), 12300; https://doi.org/10.3390/ijms252212300 - 15 Nov 2024
Viewed by 1541
Abstract
The mouse bleomycin model is useful in pre-clinical IPF research to understand pathophysiological mechanisms and pharmacological interventions. In the present study, we systematically investigated the effects of bleomycin at a 60-fold dose range on experimental features of lung fibrosis in the mouse bleomycin [...] Read more.
The mouse bleomycin model is useful in pre-clinical IPF research to understand pathophysiological mechanisms and pharmacological interventions. In the present study, we systematically investigated the effects of bleomycin at a 60-fold dose range on experimental features of lung fibrosis in the mouse bleomycin model. We analyzed the effect of intratracheal (i.t.) dosing of 0.05–3 U/kg bleomycin on disease phenotypes, including weight loss, morbidity and mortality, pulmonary inflammation, lung collagen content, various BALF biomarkers, and histology in a 14-day mouse model when the animals are in the active phase of fibrosis. In mice, challenge with 1–2 U/kg bleomycin doses induced significant and saturated responses on fibrotic endpoints, confirmed by collagen content, BALF biomarker levels, and marked weight loss compared to the normal control (NC). We observed 100% mortality in 3 U/kg of bleomycin-treated mice. In contrast, 0.05–0.5 U/kg bleomycin doses induced a dose-dependent fibrotic phenotype. The mice challenged with doses of 0.25–0.5 U/kg bleomycin showed optimum body weight loss, a significant increase in pulmonary inflammation, and the fibrotic phenotype compared to NC. Furthermore, we showed 0.25–0.5 U/kg bleomycin increases expression levels of (pro-) fibrotic cytokines, which are the mediators involved in the activation of myofibroblast during fibrogenesis (TGF-β1, IL-13, IL-6, WISP-1, VEGF), angiogenesis (VEGF), matrix remodeling (TIMP-1), and non-invasive lung function biomarker (CRP) compared to NC. A modified Ashcroft scale quantified that the fibrotic changes in the lungs were significantly higher in the lung of mice dosed at 0.25–0.5 U/kg > 0.1 U/kg bleomycin and non-significant in mice lung dosed at 0.05 U/kg bleomycin compared to NC. We demonstrated that the changes due to 0.25–0.5 U/kg i.t. bleomycin on protein biomarkers are enough to drive robust and detectable fibrotic pathology without mortality. The 0.1 U/kg has a moderate phenotype, and 0.05 U/kg had no detectable phenotype. The Goodness of Fit (r2) and Pearson correlation coefficient (r) analyses revealed a positive linear association between change evaluated in all experimental features of fibrosis and bleomycin concentrations (0.05–0.5 U/kg). Here, we provide an examination of a highly calibrated relationship between 60-fold bleomycin concentrations and a set of in vivo readouts that covers various facets of experimental fibrosis. Our study shows that there is a dose-dependent effect of bleomycin on the features of experimental fibrosis at <1 U/kg, whereas saturated responses are achieved at >1 U/kg. Our careful experimental observations, accuracy, and comprehensive data set provided meaningful insights into the effect of bleomycin dose(s) on the fibrotic phenotype, which is valuable in preclinical drug development and lung fibrosis research. In addition, we have presented a set of reproducible frameworks of endpoints that can be used for reliable assessment of the fibrotic phenotype, and in vivo therapeutic intervention(s) with improved accuracy. Full article
(This article belongs to the Special Issue State-of-the-Art Molecular Mechanisms of Pulmonary Pathology)
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Figure 1

Figure 1
<p>Effect of i.t. bleomycin concentrations on clinical signs and pulmonary inflammation. (<b>A</b>) % body weight, (<b>B</b>) % body weight loss, (<b>C</b>) leukocytes, (<b>D</b>) macrophages, (<b>E</b>) lymphocytes, (<b>F</b>) neutrophils. Data are expressed as mean ±SEM of n=5 mice/group. * <span class="html-italic">p</span> &lt; 0.05; ** <span class="html-italic">p</span> &lt; 0.01; and *** <span class="html-italic">p</span> &lt; 0.001 Vs NC.</p>
Full article ">Figure 2
<p>Effect of i.t. bleomycin concentrations on lung parameters and vascular permeability. (<b>A</b>) right lung collagen content, (<b>B</b>) wet weight of right lung, (<b>C</b>) lung index, (<b>D</b>) protein content. Data are expressed as mean ± SEM of n=5 mice/group. * <span class="html-italic">p</span> &lt; 0.05; **<span class="html-italic">p</span> &lt; 0.01; and *** <span class="html-italic">p</span> &lt;0.001 Vs NC.</p>
Full article ">Figure 3
<p>Effect of i.t. bleomycin concentrations on lung fibrosis BALF biomarkers. BALF profibrotic biomarkers (<b>A</b>) TGFβ-1, (<b>B</b>) IL-13, (<b>C</b>) IL-6, (<b>D</b>) WISP-1, (<b>E</b>) VEGF, (<b>F</b>) TIMP-1, and (<b>G</b>) CRP. Data are expressed as mean ± SEM of n = 5 mice/group. * <span class="html-italic">p</span> &lt; 0.05; ** <span class="html-italic">p</span> &lt; 0.01; and *** <span class="html-italic">p</span> &lt; 0.001 Vs NC.</p>
Full article ">Figure 4
<p>Effect of bleomycin challenge on fold change of Lung parameters and BALF biomarkers. Fold change of (<b>A</b>) collagen content, (<b>B</b>) lung weight, (<b>C</b>) lung index, (<b>D</b>) Protein, (<b>E</b>) TGFβ-1, (<b>F</b>) IL-6, (<b>G</b>) VEGF, (<b>H</b>) CRP (<b>I</b>) TIMP-1 due to 0.05-2 U/kg bleomycin challenge. The levels of (<b>J</b>) IL-13*, and fold change of (<b>K</b>) WISP-1, due to 0.05–0.5 U/kg bleomycin challenge.</p>
Full article ">Figure 5
<p>Effect of i.t. bleomycin concentrations on lung pathology and severity of fibrosis. Representative histopathological images (10× magnification) of hematoxylin (H) and eosin (E) staining of mice lung treated with (<b>A</b>) PBS; bleomycin (<b>B</b>) 0.05, (<b>C</b>) 0.1, (<b>D</b>) 0.25, (<b>E</b>) 0.5 U/kg; severity of fibrosis by Modified Ashcroft scale (<b>F</b>). Data are expressed as mean ± SEM of n = 5 mice/group. *** <span class="html-italic">p</span> &lt; 0.001 Vs NC. Scale bar:50 µm.</p>
Full article ">Figure 6
<p>Simple linear regression analysis between concentrations of bleomycin and features of experimental fibrosis. (<b>A</b>) leukocytes, (<b>B</b>) neutrophils, (<b>C</b>) lymphocytes, (<b>D</b>) macrophages, (<b>E</b>) collagen, (<b>F</b>) lung weight, (<b>G</b>) lung Index, (<b>H</b>) protein content, (<b>I</b>) TGFβ-1, (<b>J</b>) IL-13, (<b>K</b>) IL-6, (<b>L</b>) WISP-1, (<b>M</b>) VEGF, (<b>N</b>) TIMP-1, (<b>O</b>) CRP, (<b>P</b>) Modified Ashcroft Scale. Goodness of Fit: <span class="html-italic">r</span><sup>2</sup>, Pearson correlation coefficient (<span class="html-italic">r</span>), n = 5/group.</p>
Full article ">
15 pages, 11742 KiB  
Article
Role of WISP1 in Stellate Cell Migration and Liver Fibrosis
by Daniela González, Gisela Campos, Larissa Pütter, Adrian Friebel, Christian H. Holland, Leonhard Holländer, Ahmed Ghallab, Zaynab Hobloss, Maiju Myllys, Stefan Hoehme, Nadja M. Meindl-Beinker, Steven Dooley, Rosemarie Marchan, Thomas S. Weiss, Jan G. Hengstler and Patricio Godoy
Cells 2024, 13(19), 1629; https://doi.org/10.3390/cells13191629 - 29 Sep 2024
Cited by 1 | Viewed by 1207
Abstract
The mechanisms underlying the remarkable capacity of the liver to regenerate are still not completely understood. Particularly, the cross-talk between cytokines and cellular components of the process is of utmost importance because they represent potential avenues for diagnostics and therapeutics. WNT1-inducible-signaling pathway protein [...] Read more.
The mechanisms underlying the remarkable capacity of the liver to regenerate are still not completely understood. Particularly, the cross-talk between cytokines and cellular components of the process is of utmost importance because they represent potential avenues for diagnostics and therapeutics. WNT1-inducible-signaling pathway protein 1 (WISP1) is a cytokine member of the CCN family, a family of proteins that play many different roles in liver pathophysiology. WISP1 also belongs to the earliest and strongest upregulated genes in mouse livers after CCl4 intoxication and has recently been shown to be secreted by tumor cells and to bind to type 1 collagen to cause its linearization in vitro and in tumor tissue in vivo. We show that WISP1 expression is strongly induced by TGFβ, a critical cytokine in wound healing processes. Additionally, secretion of WISP1 protein by hepatic stellate is increased in cells upon TGFβ stimulation (~seven-fold increase). Furthermore, WISP1 facilitates the migration of mouse hepatic stellate cells through collagen in vitro. However, in WISP1 knockout mice, no difference in stellate cell accumulation in damaged liver tissue and no influence on fibrosis was obtained, probably because the knockout of WISP1 was compensated by other factors in vivo. Full article
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Figure 1

Figure 1
<p>Expression and secretion of WNT1-inducible-signaling pathway protein 1 (WISP1) by hepatocytes and non-parenchymal cell types. (<b>A</b>) Gene array data of mice at various time periods after administration of CCl<sub>4</sub> (1.6 g/kg) and confirmation of WISP1 mRNA levels by qRT-PCR. The individual fuzzy clusters contain genes with a similar time course after the administration of CCl<sub>4</sub>. This heatmap is adapted from a previous publication. Data are means ± SE of three mice per time point. (<b>B</b>) Induction of WISP1 RNA levels by an overdose of paracetamol (APAP; 300 mg/kg). Data are means ± SE of three mice per time point. (<b>C</b>) PCR analysis of WISP1 mRNA in mouse liver after CCl<sub>4</sub> administration or in primary hepatocytes after TGFβ stimulation with the indicated concentrations for 24 h. The primers used were designed to flank the full-length transcript of WISP1. (<b>D</b>) Verification of the specificity of the WISP1 antibody by siRNA-mediated knockdown in cultured hepatocytes. Data represent three independent experiments. (<b>E</b>) Enrichment of liver sinusoidal endothelial cells (LSECs), Kupffer cells (KCs), hepatic stellate cells (HSCs), hepatocytes (HEP), and non-parenchymal cells (NPCs); (mixed) and characterization by the markers CD146, ADGRE1 and desmin (qRT-PCR). Data are means ± SE of three independent experiments. (<b>F</b>) Expression (qRT-PCR) and (<b>G</b>) secretion (ELISA) of WISP1 by cultured hepatocytes (Heps), LSECs, KCs, and HSCs (48 h) with and without stimulation by TGFβ. Data are means ± SE of three independent experiments. * <span class="html-italic">p</span> &lt; 0.05; ** <span class="html-italic">p</span> &lt; 0.01; *** <span class="html-italic">p</span> &lt; 0.001 to control, unpaired <span class="html-italic">t</span>-test.</p>
Full article ">Figure 2
<p>WNT1-inducible-signaling pathway protein 1 (WISP1) influences the migration of stellate cells through collagen in vitro. (<b>A</b>) Experimental design. (<b>B</b>) Influence of collagen and WISP1 on the passage of hepatic stellate cells (HSCs) through the membrane. (<b>C</b>) Influence of WISP1 on the amount of collagen on membranes. (<b>D</b>) Influence of WISP1 and TGFβ (positive control) on the expression of α-SMA, Col1a1, and WISP1. The data are presented as means ± standard errors of 3 biological replicates. * <span class="html-italic">p</span> &lt; 0.05; ** <span class="html-italic">p</span> &lt; 0.01; *** <span class="html-italic">p</span> &lt; 0.001 to control, one-way ANOVA. Compared to the control with 1.5 mg/mL Col I, BSA (50 µg/mL), without WISP1, the sample with 50 µg/mL of WISP1 shows significantly higher migration (<span class="html-italic">p</span> &lt; 0.01).</p>
Full article ">Figure 3
<p>WNT1-inducible-signaling pathway protein 1 (WISP1) knockout in acute liver damage. (<b>A</b>) Knockout strategy (<b>B</b>) verification of the knockout strategy by PCR and (<b>C</b>) qRT-PCR of WISP1 in various organs. (<b>D</b>) Experimental design of acute APAP overdose and verification of the WISP1 knockout by qRT-PCR, * <span class="html-italic">p</span> &lt; 0.05, one-way ANOVA. (<b>E</b>) Macroscopic appearance of the livers of WISP1 KO and WT mice as well as Hematoxylin–Eosin (H&amp;E) stainings. Scale bars 200 µm.</p>
Full article ">Figure 4
<p>Quantification of desmin and α-SMA positive cells after administration of a hepatotoxic dose of APAP. qRT-PCR of desmin and α-SMA mRNA levels in liver tissue after APAP overdose. The data are presented as means ± standard errors of three biological replicates. * <span class="html-italic">p</span> &lt; 0.05; compared to control, one-way ANOVA.</p>
Full article ">Figure 5
<p>(<b>A</b>) Visualization of quiescent and activated hepatic stellate cells (HSCs) 18, 24 and 48 h after administration of a hepatotoxic dose of acetaminophen (APAP). (<b>A</b>) Immunostaining of the quiescent HSC maker desmin. (<b>B</b>) Immunostaining of α-SMA, a marker of activated HSCs.</p>
Full article ">Figure 6
<p>WNT1-inducible-signaling pathway protein 1 (WISP1) knockout in chronic liver damage. (<b>A</b>) Experimental schedule of CCl<sub>4</sub> induced fibrosis and representative examples of fibrotic streaks. Scale bars 1000 µm (<b>B</b>) Image analysis and quantification of fibrotic streaks. Data are presented as means ± standard errors of at least three mice per group. * <span class="html-italic">p</span> &lt; 0.05; ** <span class="html-italic">p</span> &lt; 0.01; *** <span class="html-italic">p</span> &lt; 0.001, two-way ANOVA. (<b>C</b>) Expression of fibrosis-associated genes. Results are plotted as a log-fold increase compared to the control liver and are presented as means ± standard errors of at least three mice per group. * <span class="html-italic">p</span> &lt; 0.05; ** <span class="html-italic">p</span> &lt; 0.01; *** <span class="html-italic">p</span> &lt; 0.001, multiple <span class="html-italic">t</span>-test. (<b>D</b>) Activity of ALT, AST, and ALT in blood.</p>
Full article ">Figure 7
<p>Expression of the CCN (connective tissue growth factor, cysteine-rich protein, and nephroblastoma overexpressed) gene family and further collagen-binding proteins during acute and chronic exposure to CCl<sub>4</sub> (<b>A</b>) Expression of CCN proteins after single doses of CCl<sub>4</sub> and APAP. (<b>B</b>) Expression of CCN proteins and collagen-binding proteins during chronic CCl<sub>4</sub> exposure. * <span class="html-italic">p</span> &lt; 0.05; ** <span class="html-italic">p</span> &lt; 0.01; *** <span class="html-italic">p</span> &lt; 0.001, paired <span class="html-italic">t</span>-test.</p>
Full article ">
31 pages, 1061 KiB  
Review
WISP1 and Macrophage Migration Inhibitory Factor in Respiratory Inflammation: Novel Insights and Therapeutic Potentials for Asthma and COPD
by Maria-Elpida Christopoulou, Alexios J. Aletras, Eleni Papakonstantinou, Daiana Stolz and Spyros S. Skandalis
Int. J. Mol. Sci. 2024, 25(18), 10049; https://doi.org/10.3390/ijms251810049 - 18 Sep 2024
Cited by 1 | Viewed by 2826
Abstract
Recent advancements highlight the intricate interplay between the extracellular matrix (ECM) and immune responses, notably in respiratory diseases such as asthma and Chronic Obstructive Pulmonary Disease (COPD). The ECM, a dynamic structural framework within tissues, orches-trates a plethora of cellular processes, including immune [...] Read more.
Recent advancements highlight the intricate interplay between the extracellular matrix (ECM) and immune responses, notably in respiratory diseases such as asthma and Chronic Obstructive Pulmonary Disease (COPD). The ECM, a dynamic structural framework within tissues, orches-trates a plethora of cellular processes, including immune cell behavior and tissue repair mecha-nisms. WNT1-inducible-signaling pathway protein 1 (WISP1), a key ECM regulator, controls immune cell behavior, cytokine production, and tissue repair by modulating integrins, PI3K, Akt, β-catenin, and mTOR signaling pathways. WISP1 also induces macrophage migration inhibitory factor (MIF) expression via Src kinases and epidermal growth factor receptor (EGFR) activation. MIF, through its wide range of activities, enhances inflammation and tissue restructuring. Rec-ognized for its versatile roles in regulating the immune system, MIF interacts with multiple immune components, such as the NLRP3 inflammasome, thereby sustaining inflammatory pro-cesses. The WISP1–MIF axis potentially unveils complex molecular mechanisms governing im-mune responses and inflammation. Understanding the intricate roles of WISP1 and MIF in the pathogenesis of chronic respiratory diseases such as asthma and COPD could lead to the identi-fication of novel targets for therapeutic intervention to alleviate disease severity and enhance patient outcomes. Full article
(This article belongs to the Section Molecular Immunology)
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<p><b>Structure of CCN proteins.</b> A classical CCN protein features an N-terminal signaling peptide and four functional domains: (1) insulin-like growth factor-binding protein (IGFBP) domain, (2) von Willebrand factor type C (VWC) domain, (3) thrombospondin type 1 repeat (TSP-1) domain, and (4) cysteine knot carboxyl-terminal repeat (CT) domain. Each of these domains mediates interactions with various binding partners. For example, insulin-like growth factors (IGFs) bind to the IGFBP domain, while bone morphogenic protein 4 (BMP4) and transforming growth factor β (TGF-β) interact with the VWC domain. The TSP-1 domain interacts with heparin-sulfated proteoglycans (HSPGs), and the CT domain engages with LDL receptor protein 1 (LRP-1). Additionally, CCN proteins bind to a variety of cell surface receptors, including integrins, HSPGs, LRPs, and growth factors such as TGF-β, the vascular endothelial growth factor (VEGF), and BMP-4.</p>
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<p><b>WISP1 in Cellular Stress Responses.</b> WISP1, as a downstream target of WNT signaling, plays a crucial role in cytoprotection and cell survival through various molecular pathways. WISP1 binds integrins and activates the PI3K/Akt pathway, inhibiting GSK-3β and stabilizing β-catenin, which enhances the transcription of anti-apoptotic genes. WISP1 modulates apoptotic pathways by influencing mitochondrial signaling and preventing cytochrome c release, thereby inhibiting caspase activation. WISP1 also upregulates Bcl-XL, which sequesters pro-apoptotic proteins. Additionally, WISP1 mitigates p53-mediated apoptosis through PI3K/Akt activation, preventing apoptosome formation. It establishes a positive feedback loop by inducing its own expression and enhances SIRT1 activity, which modulates PI3K/Akt signaling. WISP1 suppresses FoxO3a activity through PI3K/Akt-mediated phosphorylation and interacts with the mTOR pathway, activating mTORC1 to promote cell growth and proliferation. Collectively, these mechanisms underscore the role of WISP1 in cell survival, tissue repair, and tumorigenicity; AC (acetylation); and p (phosphorylation).</p>
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16 pages, 3522 KiB  
Article
Repurposing Niclosamide to Modulate Renal RNA-Binding Protein HuR for the Treatment of Diabetic Nephropathy in db/db Mice
by Lili Zhuang, Wenjin Liu, Xiao-Qing Tsai, Connor Outtrim, Anna Tang, Zhou Wang and Yufeng Huang
Int. J. Mol. Sci. 2024, 25(17), 9651; https://doi.org/10.3390/ijms25179651 - 6 Sep 2024
Viewed by 1200
Abstract
Hu antigen R (HuR) plays a key role in regulating genes critical to the pathogenesis of diabetic nephropathy (DN). This study investigates the therapeutic potential of niclosamide (NCS) as an HuR inhibitor in DN. Uninephrectomized mice were assigned to four groups: normal control; [...] Read more.
Hu antigen R (HuR) plays a key role in regulating genes critical to the pathogenesis of diabetic nephropathy (DN). This study investigates the therapeutic potential of niclosamide (NCS) as an HuR inhibitor in DN. Uninephrectomized mice were assigned to four groups: normal control; untreated db/db mice terminated at 14 and 22 weeks, respectively; and db/db mice treated with NCS (20 mg/kg daily via i.p.) from weeks 18 to 22. Increased HuR expression was observed in diabetic kidneys from db/db mice, which was mitigated by NCS treatment. Untreated db/db mice exhibited obesity, progressive hyperglycemia, albuminuria, kidney hypertrophy and glomerular mesangial matrix expansion, increased renal production of fibronectin and a-smooth muscle actin, and decreased glomerular WT-1+-podocytes and nephrin expression. NCS treatment did not affect mouse body weight, but reduced blood glucose and HbA1c levels and halted the DN progression observed in untreated db/db mice. Renal production of inflammatory and oxidative stress markers (NF-κBp65, TNF-a, MCP-1) and urine MDA levels increased during disease progression in db/db mice but were halted by NCS treatment. Additionally, the Wnt1-signaling-pathway downstream factor, Wisp1, was identified as a key downstream mediator of HuR-dependent action and found to be markedly increased in db/db mouse kidneys, which was normalized by NCS treatment. These findings suggest that inhibition of HuR with NCS is therapeutic for DN by improving hyperglycemia, renal inflammation, and oxidative stress. The reduction in renal Wisp1 expression also contributes to its renoprotective effects. This study supports the potential of repurposing HuR inhibitors as a novel therapy for DN. Full article
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<p>Increased renal HuR staining, and protein production were observed in the diabetic db/db mouse kidney. (<b>A</b>) Representative photomicrographs of renal immunofluorescent staining for HuR (red) at 400× magnification are shown from normal mice (NC), diabetic db/db mice at 14 weeks (db/db–14wk), diabetic db/db mice at 22 weeks (db/db–22wk) and diabetic db/db mice treated with NCS at 22 weeks (db/db + NCS–22wk). A few cells with cytoplasmic staining for HuR are indicated by arrows in the diabetic kidneys. (<b>B</b>) Representative Western blots illustrate the total cellular protein expression of HuR and ß-actin in the renal cortex tissue. (<b>C</b>) Quantification of the Western blot band density. Protein values are expressed as fold-changes relative to the normal control, which was set to unity. * <span class="html-italic">p</span> &lt; 0.05, vs. NC; # <span class="html-italic">p</span> &lt; 0.05, vs. db/db–14wk; £ <span class="html-italic">p</span> &lt; 0.05, vs. db/db–22wk.</p>
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<p>Treatment with NCS arrests the progression of albuminuria in diabetic db/db mice. Urine and urinary albumin excretion levels over 24 h (UAE/24 h) were collected and determined at the ages of 14, 18, and 22 weeks, as described in the <a href="#sec4-ijms-25-09651" class="html-sec">Section 4</a>. * <span class="html-italic">p</span> &lt; 0.05, vs. NC; # <span class="html-italic">p</span> &lt; 0.05, vs. db/db–14wk; £ <span class="html-italic">p</span> &lt; 0.05, vs. db/db–22wk.</p>
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<p>Treatment with NCS reduces glomerular hypertrophy, glomerulosclerosis, glomerular matrix protein deposition and expression in diabetic db/db mice. (<b>A</b>) The representative microscopic images illustrate PAS staining of kidney sections, which was used to detect glomerular size and extracellular matrix (ECM) deposition (stained pink). Magnification, ×400. (<b>B</b>) Representative photomicrographs of glomerular immunofluorescent staining for type IV collagen (Col-IV). Magnification, ×400. (<b>C</b>–<b>E</b>) The graphs summarize the results of average glomerular size (<b>C</b>), glomerular ECM deposition (<b>D</b>) and glomerular Col-IV staining score (<b>E</b>), quantified using image-J. (<b>F</b>) Western blots of FN, a-SMA, and ß-actin from normal mouse kidneys and diabetic kidneys of untreated and treated mice. Molecular weight is labelled on the right. (<b>G</b>,<b>H</b>) The graphs present the results of band density measurements for FN (<b>G</b>) and a-SMA (<b>H</b>) in the kidneys. The protein values are expressed relative to normal control, which was set to unity. (<b>I</b>–<b>K</b>) The graphs show the relative mRNA levels of FN (<b>I</b>), Collagen I-a1 (Col-I) (<b>J</b>), and Collagen IV-a1 (Col-IV) (<b>K</b>) in the kidneys, as determined by the real-time RT–PCR assay. * <span class="html-italic">p</span> &lt; 0.05, vs. NC; # <span class="html-italic">p</span> &lt; 0.05, vs. db/db–14wk; £ <span class="html-italic">p</span> &lt; 0.05, vs. db/db–22wk.</p>
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<p>Treatment with NCS reverses the glomerular podocyte number and nephrin expression in diabetic db/db mice. (<b>A</b>) Kidney sections from normal mice (NC), diabetic db/db mice at 14 weeks (db/db–14wk), diabetic db/db mice at 22 weeks (db/db–22wk) and diabetic db/db mice treated with NCS at 22 weeks (db/db + NCS–22wk) were stained with nephrin and WT-1-postive podocytes. Magnification, 400×. (<b>B</b>,<b>C</b>) The graphs summarize the results of glomerular nephrin staining (<b>B</b>) and WT-1<sup>+</sup> cells (<b>C</b>), quantified using image-J. * <span class="html-italic">p</span> &lt; 0.05, vs. NC; # <span class="html-italic">p</span> &lt; 0.05, vs. db/db–14wk; £ <span class="html-italic">p</span> &lt; 0.05, vs. db/db–22wk.</p>
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<p>Treatment with NCS reduces renal NF-kBp65 and Nox2 protein production in diabetic db/db mice. (<b>A</b>) Representative Western blots illustrate the protein expression of NF-kBp65, Nox2 and ß-actin in the kidney tissue from normal mice and diabetic untreated and treated mice. Molecular weight is labelled on the right. (<b>B</b>,<b>C</b>) The graphs present the results of band density measurements for NF-kBp65 (<b>B</b>) and Nox2 (<b>C</b>) in the kidneys. Protein values are expressed relative to normal control, which was set to unity. * <span class="html-italic">p</span> &lt; 0.05, vs. NC; # <span class="html-italic">p</span> &lt; 0.05, vs. db/db–14wk; £ <span class="html-italic">p</span> &lt; 0.05, vs. db/db–22wk.</p>
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<p>Treatment with NCS ameliorates renal angiopoietin (Angpt) 1 and 2 expression in diabetic db/db mice. (<b>A</b>) Representative Western blots illustrate the protein expression of Angpt1, Angpt2 and ß-actin in the kidney tissue from normal mice and diabetic untreated and treated mice. Molecular weight is labelled on the right. (<b>B</b>–<b>D</b>) The graphs present the results of band density measurements for Angpt1 (<b>B</b>), Angpt2 (<b>C</b>) and the ratio of Angpt1 to Angpt2 (<b>D</b>) in the kidneys. Protein values are expressed relative to normal control, which was set to unity. * <span class="html-italic">p</span> &lt; 0.05, vs. NC; # <span class="html-italic">p</span> &lt; 0.05, vs. db/db–14wk; £ <span class="html-italic">p</span> &lt; 0.05, vs. db/db–22wk.</p>
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<p>Treatment with NCS reduces renal mRNA and protein expression of Wisp1 in diabetic db/db mice. (<b>A</b>) The graph shows the relative mRNA levels of Wisp1 in the kidneys, as determined by the real-time RT–PCR assay. (<b>B</b>) Representative Western blots illustrate the protein expression of Wisp1 and GAPDH in the kidney tissue from normal mice and diabetic untreated and treated mice. Molecular weight is labelled on the right. (<b>C</b>) The graph summarizes the results of band density measurements for Wisp1 and GAPDH in the kidneys. Protein values are expressed relative to normal control, which was set to unity. * <span class="html-italic">p</span> &lt; 0.05, vs. NC; # <span class="html-italic">p</span> &lt; 0.05, vs. db/db–14wk; £ <span class="html-italic">p</span> &lt; 0.05, vs. db/db–22wk.</p>
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15 pages, 1081 KiB  
Review
Latest Advances in Chondrocyte-Based Cartilage Repair
by Li Yue, Ryan Lim and Brett D. Owens
Biomedicines 2024, 12(6), 1367; https://doi.org/10.3390/biomedicines12061367 - 19 Jun 2024
Cited by 3 | Viewed by 3364
Abstract
Chondrocyte-based cell therapy has been used for more than 30 years and is still considered to be a promising method of cartilage repair despite some limitations. This review introduces the latest developments of four generations of autologous chondrocyte implantation and current autologous chondrocyte [...] Read more.
Chondrocyte-based cell therapy has been used for more than 30 years and is still considered to be a promising method of cartilage repair despite some limitations. This review introduces the latest developments of four generations of autologous chondrocyte implantation and current autologous chondrocyte products. The regeneration of cartilage from adult chondrocytes is limited by culture-induced dedifferentiation and patient age. Cartibeads is an innovative three-step method to produce high-quality hyaline cartilage microtissues, and it is developed from adult dedifferentiated chondrocytes with a high number of cell passages. In addition, allogeneic chondrocyte therapies using the Quantum hollow-fiber bioreactor and several signaling pathways involved in chondrocyte-based cartilage repair are mentioned, such as WNT signaling, the BMP-2/WISP1 pathway, and the FGF19 pathway. Full article
(This article belongs to the Special Issue Advances in Chondrocyte Biology)
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<p>Schemes of the 3-step method for the generation of Cartibeads (<b>A</b>) and BMP-2/WISP1 and FGF19 signaling pathways (<b>B</b>).</p>
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17 pages, 7054 KiB  
Article
WISP-1 Regulates Cardiac Fibrosis by Promoting Cardiac Fibroblasts’ Activation and Collagen Processing
by Ze Li, Helen Williams, Molly L. Jackson, Jason L. Johnson and Sarah J. George
Cells 2024, 13(11), 989; https://doi.org/10.3390/cells13110989 - 6 Jun 2024
Viewed by 1752
Abstract
Hypertension induces cardiac fibrotic remodelling characterised by the phenotypic switching of cardiac fibroblasts (CFs) and collagen deposition. We tested the hypothesis that Wnt1-inducible signalling pathway protein-1 (WISP-1) promotes CFs’ phenotypic switch, type I collagen synthesis, and in vivo fibrotic remodelling. The treatment of [...] Read more.
Hypertension induces cardiac fibrotic remodelling characterised by the phenotypic switching of cardiac fibroblasts (CFs) and collagen deposition. We tested the hypothesis that Wnt1-inducible signalling pathway protein-1 (WISP-1) promotes CFs’ phenotypic switch, type I collagen synthesis, and in vivo fibrotic remodelling. The treatment of human CFs (HCFs, n = 16) with WISP-1 (500 ng/mL) induced a phenotypic switch (α-smooth muscle actin-positive) and type I procollagen cleavage to an intermediate form of collagen (pC-collagen) in conditioned media after 24h, facilitating collagen maturation. WISP-1-induced collagen processing was mediated by Akt phosphorylation via integrin β1, and disintegrin and metalloproteinase with thrombospondin motifs 2 (ADAMTS-2). WISP-1 wild-type (WISP-1+/+) mice and WISP-1 knockout (WISP-1−/−) mice (n = 5–7) were subcutaneously infused with angiotensin II (AngII, 1000 ng/kg/min) for 28 days. Immunohistochemistry revealed the deletion of WISP-1 attenuated type I collagen deposition in the coronary artery perivascular area compared to WISP-1+/+ mice after a 28-day AngII infusion, and therefore, the deletion of WISP-1 attenuated AngII-induced cardiac fibrosis in vivo. Collectively, our findings demonstrated WISP-1 is a critical mediator in cardiac fibrotic remodelling, by promoting CFs’ activation via the integrin β1-Akt signalling pathway, and induced collagen processing and maturation via ADAMTS-2. Thereby, the modulation of WISP-1 levels could provide potential therapeutic targets in clinical treatment. Full article
(This article belongs to the Section Tissues and Organs)
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<p>WISP-1 protein induced type I collagen processing in conditioned media of human cardiac fibroblasts (HCFs). HCFs were cultured in supplemented fibroblast growth medium for 24 h and then in serum-free medium (SFM) for 48 h. The medium was replaced with fresh SFM in the presence or absence of recombinant human WISP-1 protein (500 ng/mL) for 24 h, and conditioned media were collected and concentrated for Western blotting. Stain-free gel bands from corresponding cell lysate samples were used as the loading control. Representative Western blots of (<b>A</b>) type I procollagen and pC-collagen (tropocollagen with PICP), detected using anti-C-telo antibody (n = 16), (<b>B</b>) type I procollagen, pC-collagen (tropocollagen with PICP), and PICP, detected using anti-PICP antibody (n = 8), and (<b>C</b>) type I procollagen, detected using anti-PINP antibody (n = 8). Schematic molecular structures and approximate molecular weights in kDa are indicated adjacent to representative immunoblots.</p>
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<p>Silencing ADAMTS-2 inhibited WISP-1 protein-induced type I collagen processing in conditioned media of human cardiac fibroblasts (HCFs). HCFs were either transfected with control SiRNA (1.228 μM), ADAMTS SiRNAs (614 nM/target gene), or left untransfected prior to seeding on a 12-well plate. After culture in supplemented fibroblast growth medium for 24 h, HCFs were starved in serum-free medium (SFM) for 48 h. The medium was then replaced with fresh SFM in the presence or absence of recombinant human WISP-1 protein (500 ng/mL) and HCFs cultured for 15 h for qPCR analysis, and 24 h or 96 h for Western blotting analysis. (<b>A</b>) Quantification of ADAMTS-2 mRNA expression using qPCR analysis. Data were normalised to 36B4 housekeeping gene and expressed as the relative fold change to the untransfected HCFs (Control). (<b>B</b>) Quantification of ADAMTS-2 protein expression (168 h post-transfection) using Western blotting analysis. Data were normalised to stain-free gel bands and expressed as the relative fold change to the untransfected HCFs (Control). (<b>C</b>) Representative Western blots of type I procollagen and pC-collagen (tropocollagen with PICP) detected using anti-C-telo antibody. Stain-free gel bands from corresponding cell lysate samples were used as loading control. Quantification of pC-collagen I protein expression (96 h post-transfection) was expressed as the relative fold change to the WISP-1 protein treatment group. Data shown as mean ± SEM (n = 4–6). Statistical analysis was performed using Kruskal–Wallis H test. * indicates <span class="html-italic">p</span> &lt; 0.05. Approximate molecular weights in kDa are indicated adjacent to representative immunoblots.</p>
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<p>WISP-1 protein promoted Akt phosphorylation via integrin β1/FAK/ILK in human cardiac fibroblasts (HCFs). HCFs were cultured in supplemented fibroblast growth medium for 24 h and then starved in serum-free medium (SFM) for 48 h. The medium was replaced with fresh SFM in the presence or absence of recombinant human WISP-1 protein (500 ng/mL) for 30 min before cell lysis. Cell lysate samples were analysed by Western blotting using phosphorylated Akt (p-Akt) (Ser473) and total Akt (t-Akt) antibodies. (<b>A</b>) Representative Western blots of p-Akt (Ser473) and t-Akt protein expression. The ratio of p-Akt (Ser473) to t-Akt was calculated and expressed as the relative fold change to the control. Data shown as mean ± SEM (n = 9). Statistical analysis was performed using Mann–Whitney U test. * indicates <span class="html-italic">p</span> &lt; 0.05. (<b>B</b>) Representative Western blots of p-Akt (Ser473) and t-Akt protein expression. The ratio of p-Akt (Ser473) to t-Akt was calculated and expressed as the relative fold change to WISP-1 + mouse non-immune IgG<sub>1</sub> control (mIgG) group. HCFs were pre-incubated with integrin β1-blocking antibodies (mouse IgG<sub>1</sub> clone) (β1 mAb, 10 μg/mL), integrin αVβ5-blocking antibodies (mouse IgG<sub>1</sub> clone) (αVβ5 mAb, 10 μg/mL), and mIgG control antibodies (10 μg/mL), respectively, for 30 min prior to WISP-1 protein treatment. Data shown as mean ± SEM (n = 5). Statistical analysis was performed using Kruskal–Wallis H test. * indicates <span class="html-italic">p</span> &lt; 0.05. (<b>C</b>) Representative Western blots of p-Akt (Ser473) and t-Akt protein expression. The ratio of p-Akt (Ser473) to t-Akt was calculated and expressed as the relative fold change to WISP-1 group. HCFs were pre-incubated with defactinib (5 μM) or CPD22 (2.5 μM) for 30 min prior to WISP-1 protein treatment. Data shown as mean ± SEM (n = 4). Statistical analysis was performed using Mann–Whitney U test. * indicates <span class="html-italic">p</span> &lt; 0.05. Approximate molecular weights in kDa are indicated adjacent to representative immunoblots.</p>
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<p>WISP-1 protein promoted human cardiac fibroblasts (HCFs) activation. HCFs were cultured on soft substrate plates (8 kPa) in supplemented fibroblast growth medium for 24 h. HCFs were starved in serum-free medium (SFM) for 48 h, then the medium was replaced with fresh SFM in the presence or absence of recombinant human WISP-1 protein (500 ng/mL) and cultured for 24 h. (<b>A</b>) HCFs were fixed for immunocytochemical staining with anti-α-SMA antibody. α-SMA positive cells are stained green, and nuclei are stained blue with DAPI (4′,6-diamidino-2-phenylindole). Some positive cells are indicated by white arrows. Scale bar represents 50 μm. Quantification of positive α-SMA staining was expressed as the relative fold change to the control of the percentage of positive α-SMA staining cells to total cells on soft substrate. Data shown as mean ± SEM (n = 8). Statistical analysis was performed using Mann–Whitney U test. * indicates <span class="html-italic">p</span> &lt; 0.05. (<b>B</b>) Quantification of α-SMA protein expression and (<b>C</b>) quantification of PCNA protein expression using Western blotting analysis. Data were normalised to stain-free gel bands and expressed as the relative fold change to the control. Data shown as mean ± SEM (n = 9). Statistical analysis was performed using Mann–Whitney U test. * indicates <span class="html-italic">p</span> &lt; 0.05. (<b>D</b>) Quantification of accumulated migration distance per cell over the duration of consecutive images (21 h 30 min). Data shown as mean ± SEM (n = 4). Statistical analysis was performed using Student’s <span class="html-italic">t</span> test. * indicates <span class="html-italic">p</span> &lt; 0.05.</p>
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<p>WISP-1 deficiency attenuated angiotensin II (AngII)-induced coronary artery perivascular fibrosis. Cardiac fibrosis was induced by subcutaneous AngII infusion (1000 ng/kg/min) for 28 days via osmotic pumps in WISP-1<sup>+/+</sup> and WISP-1<sup>−/−</sup> mice. Representative images showing type I collagen (dark brown) staining using anti-C-telo antibody in left ventricular tissues with and without AngII infusion. Nuclei are stained blue with haematoxylin. Non-immune IgG was used as the negative control. Quantification of positive type I collagen staining was expressed as the percentage of positive collagen I staining area to total tissue area. Data shown as mean ± SEM (n = 5–8). Red arrows indicate some positive staining (dark brown). Scale bar represents 100 μm. Statistical analysis was performed using Kruskal–Wallis H test. * indicates <span class="html-italic">p</span> &lt; 0.05.</p>
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<p>A schematic summary of the findings of this study. WISP-1 promotes cardiac fibroblasts’ phenotypic switch from quiescent fibroblasts to myofibroblasts (activated fibroblasts), promoting collagen processing and accumulation. WISP-1 activates Akt signalling via integrin β1/FAK/ILK in cardiac fibroblasts. Deletion of WISP-1 attenuates angiotensin II (AngII)-induced cardiac fibrotic remodelling in vivo. Figure key is illustrated on the top left-hand side of the figure. Purple ↓ denotes promotion; black ↑ denotes increase; ┤ denotes inhibition.</p>
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19 pages, 8950 KiB  
Article
Insights into Disease Progression of Translational Preclinical Rat Model of Interstitial Pulmonary Fibrosis through Endpoint Analysis
by Anil H. Kadam and Jan E. Schnitzer
Cells 2024, 13(6), 515; https://doi.org/10.3390/cells13060515 - 15 Mar 2024
Cited by 3 | Viewed by 2895
Abstract
Idiopathic pulmonary fibrosis (IPF) is a devastating interstitial lung disease characterized by the relentless deposition of extracellular matrix (ECM), causing lung distortions and dysfunction. Animal models of human IPF can provide great insight into the mechanistic pathways underlying disease progression and a means [...] Read more.
Idiopathic pulmonary fibrosis (IPF) is a devastating interstitial lung disease characterized by the relentless deposition of extracellular matrix (ECM), causing lung distortions and dysfunction. Animal models of human IPF can provide great insight into the mechanistic pathways underlying disease progression and a means for evaluating novel therapeutic approaches. In this study, we describe the effect of bleomycin concentration on disease progression in the classical rat bleomycin model. In a dose–response study (1.5, 2, 2.5 U/kg i.t), we characterized lung fibrosis at day 14 after bleomycin challenge using endpoints including clinical signs, inflammatory cell infiltration, collagen content, and bronchoalveolar lavage fluid-soluble profibrotic mediators. Furthermore, we investigated fibrotic disease progression after 2 U/kg i.t. bleomycin administration at days 3, 7, and 14 by quantifying the expression of clinically relevant signaling molecules and pathways, epithelial mesenchymal transition (EMT) biomarkers, ECM components, and histopathology of the lung. A single bleomycin challenge resulted in a progressive fibrotic response in rat lung tissue over 14 days based on lung collagen content, histopathological changes, and modified Ashcroft score. The early fibrogenesis phase (days 3 to 7) is associated with an increase in profibrotic mediators including TGFβ1, IL6, TNFα, IL1β, CINC1, WISP1, VEGF, and TIMP1. In the mid and late fibrotic stages, the TGFβ/Smad and PDGF/AKT signaling pathways are involved, and clinically relevant proteins targeting galectin-3, LPA1, transglutaminase-2, and lysyl oxidase 2 are upregulated on days 7 and 14. Between days 7 and 14, the expressions of vimentin and α-SMA proteins increase, which is a sign of EMT activation. We confirmed ECM formation by increased expressions of procollagen-1Aα, procollagen-3Aα, fibronectin, and CTGF in the lung on days 7 and 14. Our data provide insights on a complex network of several soluble mediators, clinically relevant signaling pathways, and target proteins that contribute to drive the progressive fibrotic phenotype from the early to late phase (active) in the rat bleomycin model. The framework of endpoints of our study highlights the translational value for pharmacological interventions and mechanistic studies using this model. Full article
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<p>Effects of intratracheal (i.t) bleomycin concentrations on clinical signs and BALF pulmonary inflammation on day 14. Rats received the indicated amount of bleomycin i.t., as described in Materials and Methods. Body weight was measured daily, and inflammatory cells were counted after BAL on day 14. (<b>A</b>) % body weight, (<b>B</b>) % avg. body weight, (<b>C</b>) total leukocytes, (<b>D</b>) neutrophils, (<b>E</b>) lymphocytes, (<b>F</b>) macrophages. * <span class="html-italic">p</span> &lt; 0.05; ** <span class="html-italic">p</span> &lt; 0.01; and *** <span class="html-italic">p</span> &lt; 0.001 vs. NC. <span class="html-italic">n</span> = 5 rats/group.</p>
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<p>Effects of i.t bleomycin concentrations on lung parameters and vascular leakiness on day 14. Rats were treated with bleomycin, as described in <a href="#cells-13-00515-f001" class="html-fig">Figure 1</a>. After 14 days, lungs were harvested and BALF obtained. See Materials and Methods. (<b>A</b>) lung collagen content, (<b>B</b>) right lung (wet) weight, (<b>C</b>) lung index, (<b>D</b>) BALF protein content. * <span class="html-italic">p</span> &lt; 0.05; ** <span class="html-italic">p</span> &lt; 0.01; and *** <span class="html-italic">p</span> &lt; 0.001 vs. NC. <span class="html-italic">n</span> = 5 rats/group.</p>
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<p>Effects of i.t bleomycin concentrations on BALF profibrotic/ fibrotic meditators on day 14. (<b>A</b>) TGFβ1, (<b>B</b>) IL6, (<b>C</b>) TNFα, (<b>D</b>) IL1β, (<b>E</b>) CINC1, (<b>F</b>) WISP1, (<b>G</b>) VEGF, (<b>H</b>) TIMP1. * <span class="html-italic">p</span> &lt; 0.05; ** <span class="html-italic">p</span> &lt; 0.01; and *** <span class="html-italic">p</span> &lt; 0.001 vs. NC. <span class="html-italic">n</span> = 5 rats/group.</p>
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<p>Effects of i.t. bleomycin on clinical signs and pulmonary inflammation on days 3, 7, and 14. (<b>A</b>) % body weight, (<b>B</b>) % avg. body weight loss, (<b>C</b>) total leukocytes, (<b>D</b>) neutrophils, (<b>E</b>) lymphocytes, (<b>F</b>) macrophages, (<b>G</b>) % BALF inflammatory cells. * <span class="html-italic">p</span> &lt; 0.05; ** <span class="html-italic">p</span> &lt; 0.01; and *** <span class="html-italic">p</span> &lt; 0.001 vs. day 0. <span class="html-italic">n</span> = 5 rats/group.</p>
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<p>Effects of i.t. bleomycin on lung parameters and vascular leakiness on days 3, 7, and 14. (<b>A</b>) Lung collagen content, (<b>B</b>) right lung weight, (<b>C</b>) lung index, (<b>D</b>) BALF protein content. *** <span class="html-italic">p</span> &lt; 0.001 vs. day 0. <span class="html-italic">n</span> = 5 rats/group.</p>
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<p>Effects of i.t. bleomycin on BALF profibrotic/fibrotic meditators on days 3, 7, and 14. Levels of BALF (<b>A</b>) TGFβ1, (<b>B</b>) IL 6, (<b>C</b>) TNFα, (<b>D</b>) IL1β, (<b>E</b>) CINC1, (<b>F</b>) WISP1, (<b>G</b>) VEGF, and (<b>H</b>) TIMP1. * <span class="html-italic">p</span> &lt; 0.05; ** <span class="html-italic">p</span> &lt; 0.01; and *** <span class="html-italic">p</span> &lt; 0.001 vs. day 0. <span class="html-italic">n</span> = 5 rats/group.</p>
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<p>Effects of i.t. bleomycin challenge on TGFβ, PDGF/AKT pathways, and clinically relevant protein targets linked to fibrogenesis on days 7 and 14. Individual blots were performed for each protein and normalized with the average of 3 GAPDH blots. (<b>A</b>) Protein by Western blots; relative expressions of (<b>B</b>) P-Smad2/3, (<b>C</b>) TGFβ receptor 1, (<b>D</b>) PDGF receptor β, (<b>E</b>) P-AKT, (<b>F</b>) LPA-1, (<b>G</b>) transglutaminase-2, (<b>H</b>) galectin-3, and (<b>I</b>) lysyl oxidase 2. * <span class="html-italic">p</span> &lt; 0.05; ** <span class="html-italic">p</span> &lt; 0.01; *** <span class="html-italic">p</span> &lt; 0.001, and **** <span class="html-italic">p</span> &lt; 0.0001 vs. NC. <span class="html-italic">n</span> = 5 rats/group. Ns: Non significant.</p>
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<p>Effects of i.t. bleomycin challenge on the EMT process and ECM components on days 7 and 14. Individual blots were performed for each protein and normalized with the average of 3 GAPDH blots. (<b>A</b>) Protein by Western blots; relative expression of (<b>B</b>) vimentin, (<b>C</b>) procollagen-1Aα, (<b>D</b>) procollagen-3Aα, (<b>E</b>) fibronectin, (<b>F</b>) CTGF, and (<b>G</b>) α-SMA. * <span class="html-italic">p</span> &lt; 0.05; ** <span class="html-italic">p</span> &lt; 0.01; *** <span class="html-italic">p</span> &lt; 0.001 and **** <span class="html-italic">p</span> &lt; 0.0001 vs. NC. <span class="html-italic">n</span> = 5 rats/group.</p>
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<p>Effects of i.t. bleomycin challenge on lung histology and severity of fibrosis on days 3, 7, and 14. Representative histopathological images (10× magnification) and H&amp;E lung staining are shown. (<b>A</b>) Normal rats (day 0). Rats treated with bleomycin and harvested on day 3 (<b>B</b>), day 7 (<b>C</b>), and day 14 (<b>D</b>). Severity of fibrosis post bleomycin by modified Ashcroft scale (<b>E</b>). Fibrosis was examined in upper, upper-mid, lower-mid, and lower lung sections (5 random fields per each). See Materials and Methods for details. Right block arrow: normal alveolar septa; upward block arrow: thickened alveolar septa; chevron arrow: contiguous fibrotic walls of alveolar septa; notched arrow to the left: single fibrotic masses; downward block arrow: confluent fibrotic masses; triangle: large contiguous fibrotic masses; line arrow: cellular infiltration. Data are expressed as mean ± SEM of <span class="html-italic">n</span> = 5 rats/group. *** <span class="html-italic">p</span> &lt; 0.001 vs. day 0 using an unpaired <span class="html-italic">t</span>-test). Scale bar = 50 µm.</p>
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21 pages, 3106 KiB  
Article
The Long-Term Detection of Suspended Particulate Matter Concentration and Water Colour in Gravel and Sand Pit Lakes through Landsat and Sentinel-2 Imagery
by Nicola Ghirardi, Monica Pinardi, Daniele Nizzoli, Pierluigi Viaroli and Mariano Bresciani
Remote Sens. 2023, 15(23), 5564; https://doi.org/10.3390/rs15235564 - 29 Nov 2023
Cited by 2 | Viewed by 1662
Abstract
Over the past half century, the demand for sand and gravel has led to extensive quarrying activities, creating many pit lakes (PLs) which now dot floodplains and urbanized regions globally. Despite the potential importance of these environments, systematic data on their location, morphology [...] Read more.
Over the past half century, the demand for sand and gravel has led to extensive quarrying activities, creating many pit lakes (PLs) which now dot floodplains and urbanized regions globally. Despite the potential importance of these environments, systematic data on their location, morphology and water quality remain limited. In this study, we present an extensive assessment of the physical and optical properties in a large sample of PLs located in the Po River basin (Italy) from 1990 to 2021, utilizing a combined approach of remote sensing (Landsat constellation and Sentinel-2) and traditional limnological techniques. Specifically, we focused on the concentration of Suspended Particulate Matter (SPM) and the dominant wavelength (λdom, i.e., water colour). This study aims to contribute to the analysis of PLs at a basin scale as an opportunity for environmental rehabilitation and river floodplain management. ACOLITE v.2022, a neural network particularly suitable for the analysis of turbid waters and small inland water bodies, was used to atmospherically correct satellite images and to obtain SPM concentration maps and the λdom. The results show a very strong correlation between SPM concentrations obtained in situ and those obtained from satellite images, both for data derived from Landsat (R2 = 0.85) and Sentinel-2 images (R2 = 0.82). A strong correlation also emerged from the comparison of spectral signatures obtained in situ via WISP-3 and those derived from ACOLITE, especially in the visible spectrum (443–705 nm, SA = 10.8°). In general, it appeared that PLs with the highest mean SPM concentrations and the highest mean λdom are located along the main Po River, and more generally near rivers. The results also show that active PLs exhibit a poor water quality status, especially those of small sizes (<5 ha) and directly connected to a river. Seasonal comparison shows the same trend for both SPM concentration and λdom: higher values in winter gradually decreasing until spring–summer, then increasing again. Finally, it emerged that the end of quarrying activity led to a reduction in SPM concentration from a minimum of 43% to a maximum of 72%. In this context, the combined use of Landsat and Sentinel-2 imagery allowed for the evaluation of the temporal evolution of the physical and optical properties of the PLs in a vast area such as the Po River basin (74,000 km2). In particular, the Sentinel-2 images consistently proved to be a reliable resource for capturing episodic and recurring quarrying events and portraying the ever-changing dynamics of these ecosystems. Full article
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<p>Pit lakes (PLs) divided into the eight subsample areas (blue boxes). The Po River is highlighted in light blue, green dots represent active PLs, red dots represent ceased PLs, and yellow dots represent doubtful PLs (all those are lakes that have the typical characteristics of PLs but whose origin or end of mining is uncertain). Turin (TO), Po and Orba River Park (OR), Milan (MI), Trezzo sull’Adda (TR), Brescia (BS), Mantua (MN), Modena (MO), and the Po River shaft (PO).</p>
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<p>Scatterplots between in situ data (<span class="html-italic">y</span>-axis) and satellite data (<span class="html-italic">x</span>-axis). The black triangles and black squares represent comparisons between in situ and ACOLITE SPM concentrations from Landsat (L5 and L7, calibrated) and Sentinel-2 (S2) images, respectively. “n” represents the sample size, “R<sup>2</sup>” the determination coefficient, “MAE” the mean absolute error, “RMSE” the root mean square error, “MAPE” the mean absolute percentage error, and the dashed gray lines refer to the regression lines.</p>
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<p>Scatterplots between in situ WISP-3 data (<span class="html-italic">y</span>-axis) and Sentinel-2 data (<span class="html-italic">x</span>-axis). The colored dots represent comparison between WISP-3 and ACOLITE spectral signatures for the first six bands of S2. “n” represents the sample size, “R<sup>2</sup>” the determination coefficient, “MAE” the mean absolute error, “RMSE” the root mean square error, “MAPE” the mean absolute percentage error, and the dashed gray lines refer to the regression lines.</p>
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<p>Mean SPM concentrations (<b>A</b>) and λ<sub>dom</sub> (<b>B</b>) for subsample PLs for the period 1990–2021. The blue boxes represent the eight subsample areas. In the black boxes are the mean ± st.dev, and minimum and maximum SPM concentrations for each area.</p>
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<p>Boxplots of SPM concentrations (<b>left column</b>) and dominant wavelength (<b>right column</b>) of pit lakes (PLs) in the subsample (mean values referring to 1990–2021). Shown from top to bottom are comparisons of PLs’ locations, PLs’ sizes, season (according to WFD protocol), and quarrying activity. For location, size, and season boxplots, both active (<b>left</b>) and ceased (<b>right</b>) PLs are represented. In each boxplot, the circles represent the outliers. The “<span class="html-italic">p</span>” values refer to the Kruskal–Wallis and the Mann–Whitney (for quarrying boxplots only) statistical tests. For the Kruskal–Wallis test, the significant difference between two pairs of categories (<span class="html-italic">p</span> &lt; 0.05) is indicated by the lack of identical letters.</p>
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<p>SPM concentration maps of pit lakes MI-30 (ceased) and MI-31 (active) from 2017 to 2021 referred to quarrying events. MI-30 (45.406015N, 9.237314E); MI-31 (45.403253N, 9.241183E). SPM concentration maps were obtained from Sentinel-2 Level 1 images, processed with ACOLITE (SPM_Nechad2016 algorithm).</p>
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33 pages, 2467 KiB  
Review
Cornerstone Cellular Pathways for Metabolic Disorders and Diabetes Mellitus: Non-Coding RNAs, Wnt Signaling, and AMPK
by Kenneth Maiese
Cells 2023, 12(22), 2595; https://doi.org/10.3390/cells12222595 - 9 Nov 2023
Cited by 11 | Viewed by 2581
Abstract
Metabolic disorders and diabetes (DM) impact more than five hundred million individuals throughout the world and are insidious in onset, chronic in nature, and yield significant disability and death. Current therapies that address nutritional status, weight management, and pharmacological options may delay disability [...] Read more.
Metabolic disorders and diabetes (DM) impact more than five hundred million individuals throughout the world and are insidious in onset, chronic in nature, and yield significant disability and death. Current therapies that address nutritional status, weight management, and pharmacological options may delay disability but cannot alter disease course or functional organ loss, such as dementia and degeneration of systemic bodily functions. Underlying these challenges are the onset of aging disorders associated with increased lifespan, telomere dysfunction, and oxidative stress generation that lead to multi-system dysfunction. These significant hurdles point to the urgent need to address underlying disease mechanisms with innovative applications. New treatment strategies involve non-coding RNA pathways with microRNAs (miRNAs) and circular ribonucleic acids (circRNAs), Wnt signaling, and Wnt1 inducible signaling pathway protein 1 (WISP1) that are dependent upon programmed cell death pathways, cellular metabolic pathways with AMP-activated protein kinase (AMPK) and nicotinamide, and growth factor applications. Non-coding RNAs, Wnt signaling, and AMPK are cornerstone mechanisms for overseeing complex metabolic pathways that offer innovative treatment avenues for metabolic disease and DM but will necessitate continued appreciation of the ability of each of these cellular mechanisms to independently and in unison influence clinical outcome. Full article
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<p>Multiple factors can influence the development of metabolic disease and diabetes mellitus. Factors that involve increased lifespan (≥80 years of age, improved care), aging, increased weight with obesity, lower education level, and socioeconomic status can have significant roles in the development of diabetes mellitus (DM) that affects 537 million (M) individuals. With aging-related disease, the destabilization of telomeres (with genomic degradation, senescence, and cell growth arrest) through processes of shortening ultimately leads to cellular senescence, oxidative stress (release of reactive oxygen species (ROS), and the degeneration of tissues and organs (with immune and organ repair dysfunction). In addition, other conditions that can be influenced by socioeconomic conditions (low income and increased cortisol levels) include elevations in serum cholesterol, high blood pressure, and tobacco use (insulin resistance and cardiac and vascular degeneration). A low level of education (a lack of knowledge of symptoms, care, and disease complications) and increased weight and obesity (pancreatic cell loss and inflammation) also impact DM.</p>
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<p>New treatment strategies for metabolic disease and diabetes mellitus with non-coding RNAs. Non-coding RNAs play a central role in the oversight of complex metabolic pathways that offer innovative treatment avenues for metabolic disease and diabetes mellitus (DM). Innovative considerations involve non-coding RNA pathways with microRNAs (miRNAs) and circular ribonucleic acids (circRNAs), Wnt signaling, and Wnt1 inducible signaling pathway protein 1 (WISP1) that are dependent upon programmed cell death pathways, such as apoptosis and the externalization of membrane phosphatidylserine (PS) residues on cell membranes, cellular metabolic pathways with AMP-activated protein kinase (AMPK) and nicotinamide adenine dinucleotide (NAD+) pathways with nicotinamide, and growth factor applications. These pathways intersect with one another for new therapeutic strategies, such as controlling microglial activation and limiting reactive oxygen species (ROS) generation. Microglia can be detrimental to the release of reactive oxygen species (ROS) to generate oxidative stress but also can be beneficial for the clearance of toxins (amyloid) in the brain and the reduction of inflammation. Importantly, microglial pathways are overseen by Wnt signaling and erythropoietin (EPO). Triggering receptor expressed on myeloid cells 2 (TREM2) is vital to foster microglial survival to prevent inflammation. In addition, metformin, as well as trophic factors with EPO, as examples of new therapeutic strategies, can reduce metabolic dysfunction and assist with the treatment of dementia, cardiovascular disease, multiple sclerosis, and peripheral neuropathy through the oversight of microglia, AMPK (maintains mitochondrial function), and non-coding RNA pathways.</p>
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12 pages, 9346 KiB  
Article
WISP1 Is Involved in the Pathogenesis of Kashin-Beck Disease via the Autophagy Pathway
by Ping Li, Bolun Cheng, Yao Yao, Wenxing Yu, Li Liu, Shiqiang Cheng, Lu Zhang, Mei Ma, Xin Qi, Chujun Liang, Xiaomeng Chu, Jing Ye, Shiquan Sun, Yumeng Jia, Xiong Guo, Yan Wen and Feng Zhang
Int. J. Mol. Sci. 2023, 24(22), 16037; https://doi.org/10.3390/ijms242216037 - 7 Nov 2023
Cited by 2 | Viewed by 1414
Abstract
Objective: Kashin-Beck disease (KBD) is a kind of endemic and chronic osteochondropathy in China. This study aims to explore the functional relevance and potential mechanism of Wnt-inducible signaling pathway protein 1 (WISP1) in the pathogenesis of KBD. Design: KBD and control cartilage specimens [...] Read more.
Objective: Kashin-Beck disease (KBD) is a kind of endemic and chronic osteochondropathy in China. This study aims to explore the functional relevance and potential mechanism of Wnt-inducible signaling pathway protein 1 (WISP1) in the pathogenesis of KBD. Design: KBD and control cartilage specimens were collected for tissue section observation and primary chondrocyte culture. Firstly, the morphological and histopathological observations were made under a light and electron microscope. Then, the expression levels of WISP1 as well as molecular markers related to the autophagy pathway and extracellular matrix (ECM) synthesis were detected in KBD and control chondrocytes by qRT-PCR, Western blot, and immunohistochemistry. Furthermore, the lentiviral transfection technique was applied to make a WISP1 knockdown cell model based on KBD chondrocytes. In vitro intervention experiments were conducted on the C28/I2 human chondrocyte cell line using human recombinant WISP1 (rWISP1). Results: The results showed that the autolysosome appeared in the KBD chondrocytes. The expression of WISP1 was significantly higher in KBD chondrocytes. Additionally, T-2 toxin, a risk factor for KBD onset, could up-regulate the expression of WISP1 in C28/I2. The autophagy markers ATG4C and LC3II were upregulated after the low-concentration treatment of T-2 toxin and downregulated after the high-concentration treatment. After knocking down WISP1 expression in KBD chondrocytes, MAP1LC3B decreased while ATG4C and COL2A1 increased. Moreover, the rWISP1 protein treatment in C28/I2 chondrocytes could upregulate the expression of ATG4C and LC3II at the beginning and downregulate them then. Conclusions: Our study suggested that WISP1 might play a role in the pathogenesis of KBD through autophagy. Full article
(This article belongs to the Special Issue Musculoskeletal Development and Skeletal Pathophysiologies 2.0)
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<p>The expression of WISP1 in KBD and control chondrocytes. (<b>a</b>) The scale bars are 500 μm and 100 μm individually. * <span class="html-italic">p</span> &lt; 0.05. (<b>b</b>) The mRNA expression of WISP1 in KBD and control chondrocytes. * <span class="html-italic">p</span> &lt; 0.05. <span class="html-italic">n</span> = 5. (<b>c</b>) The protein expression of WISP1 in KBD and control chondrocytes. * <span class="html-italic">p</span> &lt; 0.05. <span class="html-italic">n</span> = 5.</p>
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<p>The functional role of WISP1 in KBD chondrocyte damage. (<b>a</b>) The TEM results of KBD chondrocytes. Red arrows represent (<b>a</b>(i)) The autolysosome in KBD chondrocyte, (<b>a</b>(ii)) The mitochondria in KBD chondrocyte, and (<b>a</b>(iii)) The endoplasmic reticulum in KBD chondrocyte. The yellow arrows represent a great number of liposomes. The scale bars are 2 μm, 500 nm, and 200 nm, respectively, from left to right. (<b>b</b>) The mRNA expression of selected genes in KBD and control chondrocytes. <span class="html-italic">n</span> = 5. (<b>c</b>) The protein expression of markers in KBD and controls. <span class="html-italic">n</span> = 5. (<b>d</b>) The Western blot results of markers in KBD and controls. (<b>e</b>) The bright field and dark field of the efficiency of three targets of the WISP1 lentivirus in KBD chondrocytes. The magnification is 100×. (<b>f</b>) The mRNA expression of WISP1 in KBD chondrocytes and KBD with the WISP1 lentivirus of the negative control (NC) and three targets (WISP1-A, WISP1-B, and WISP1-C). (<b>g</b>) The mRNA expression of WISP1 and other genes in controls, KBD chondrocytes, and KBD of the WISP1-A lentivirus. <span class="html-italic">n</span> = 3. (<b>h</b>) The Western blot result from markers in WISP1 knock-down KBD chondrocytes and KBD chondrocytes. (<b>i</b>) The protein expression of WISP1 and other markers in WISP1 knock-down KBD chondrocytes and KBD chondrocytes. <span class="html-italic">n</span> = 3. * <span class="html-italic">p</span> &lt; 0.05, ** <span class="html-italic">p</span> &lt; 0.01, *** <span class="html-italic">p</span> &lt; 0.001.</p>
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<p>Effects of T-2 toxin intervention in C28/I2 human chondrocytes. (<b>a</b>) The TEM results of C28/I2 human chondrocytes. (<b>a</b>(i)) The mitochondria in control C28/I2 human chondrocytes; (<b>a</b>(ii)) The autolysosome (red arrows) in C28/I2 chondrocytes treated with T-2 toxin (2 ng/mL); (<b>a</b>(iii)) The autolysosome (red arrows) in C28/I2 chondrocytes treated with T-2 toxin (5 ng/mL); (<b>a</b>(iv)) The mitochondria in C28/I2 chondrocytes treated with T-2 toxin (8 ng/mL). The scale bars are 2 μm, 500 nm, and 200 nm, respectively, from left to right. (<b>b</b>) The mRNA expression of target genes in C28/I2 intervened by T-2 toxin. (<b>c</b>) The protein expression of target markers in C28/I2 intervened by T-2 toxin. (<b>d</b>) The results of Western blots in C28/I2 intervened by T-2 toxin. * <span class="html-italic">p</span> &lt; 0.05, ** <span class="html-italic">p</span> &lt; 0.01, *** <span class="html-italic">p</span> &lt; 0.001, **** <span class="html-italic">p</span> &lt; 0.0001.</p>
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<p>The combined effect of rWISP1 with or without T-2 toxin in C28/I2 human chondrocytes. The mRNA expression of <span class="html-italic">WISP1</span> (<b>a</b>), <span class="html-italic">COL2A1</span> (<b>b</b>), <span class="html-italic">ATG4A</span> (<b>c</b>), <span class="html-italic">ATG4B</span> (<b>d</b>), <span class="html-italic">ATG4C</span> (<b>e</b>), <span class="html-italic">BECN1</span> (<b>f</b>), and <span class="html-italic">MAP1LC3B</span> (<b>g</b>) in C28/I2 was influenced by the four different concentrations of rWISP1 protein with or without three different concentrations of T-2 toxin. The abscissa stands for the four different concentrations of rWISP1 protein (5, 20, 100, and 500 ng/mL). The black, green, red, and blue lines stand for 0, 2, 5, and 8 ng/mL of T-2 toxin separately. NS stands for no sense. * <span class="html-italic">p</span> &lt; 0.05, ** <span class="html-italic">p</span> &lt; 0.01, *** <span class="html-italic">p</span> &lt; 0.001, **** <span class="html-italic">p</span> &lt; 0.0001.</p>
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15 pages, 3979 KiB  
Article
Implementation of a Wideband Microwave Filter Design with Dual Electromagnetic Interference (EMI) Mitigation for Modern Wireless Communication Systems with Low Insertion Loss and High Selectivity
by Abdul Basit, Amil Daraz and Guoqiang Zhang
Micromachines 2023, 14(11), 1986; https://doi.org/10.3390/mi14111986 - 26 Oct 2023
Cited by 2 | Viewed by 1513
Abstract
By leveraging the advantages of the uniform transmission line, this manuscript presents a broadband high-selectivity filter range starting from 2.5 GHz to 16.8 GHz, utilizing a simple uniform transmission line structure loaded with three-quarter-wavelength stubs. The proposed UWB filter is studied using the [...] Read more.
By leveraging the advantages of the uniform transmission line, this manuscript presents a broadband high-selectivity filter range starting from 2.5 GHz to 16.8 GHz, utilizing a simple uniform transmission line structure loaded with three-quarter-wavelength stubs. The proposed UWB filter is studied using the ABCD network parameter method. After that, a shorted T-shaped stub-loaded resonator is coupled with the transmission line of the UWB filter to obtain dual-notch features at 4.4 GHz (for long distance wireless ISPs (WISPs), 4G/5G operator for LTE backhaul) and 7.5 GHz (for X-band downlink communication). The overall footprint is specified as 22.5 mm × 12 mm or 1.12 λg × 0.6 λg, where λg represents the wavelength at the central frequency. The operating principle of such a filter is explained, and its controllable broadband response, as well as controllable stopband frequencies, are optimized to show some of the attractive features of the new scheme, such as a super wideband response of about a 148.18% fractional bandwidth; an out-of-band performance up to 25 GHz; five single-resonator transmission poles filtering behaviour at different frequencies, with highly reduced radiation losses greater than 10 dB; a simple topology; a flat group delay; a low insertion loss of 0.4 dB; and high selectivity. Additionally, the filter is fabricated and evaluated, and the results show a good match for experimental validation purposes. Full article
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<p>Proposed SWB-BPF architecture.</p>
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<p>Equivalent configuration of the proposed prototype.</p>
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<p>(<b>a</b>) Open-stub configuration connected to UTL; (<b>b</b>) short-circuited stub connected to UTL.</p>
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<p>(<b>a</b>) Conventional stub. (<b>b</b>) Proposed shunt stub.</p>
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<p>S-parameter responses: (<b>a</b>) response of the wideband filter loaded using a single conventional stub; (<b>b</b>) response of the proposed broadband filter.</p>
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<p>(<b>a</b>) Quarter-wavelength T-shaped resonator; (<b>b</b>) equivalent even mode; (<b>c</b>) equivalent odd-mode model.</p>
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<p>Proposed dual-notch filter.</p>
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<p>Simulated dual-stopband response.</p>
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<p>Notch band control: (<b>a</b>) response of the first stopband with controllable features; (<b>b</b>) response of the second stopband with controllable features.</p>
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<p>Coupling coefficient (k) plot with respect to the gap (G).</p>
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<p>(<b>a</b>) Frequency vs. group delay response. (<b>b</b>) Frequency vs. phase response of the SWB filter.</p>
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<p>(<b>a</b>) Frequency vs. group delay response. (<b>b</b>) Frequency vs. phase response of the SWB filter.</p>
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<p>Current distribution graph of the ultra-passband at 9.65 GHz.</p>
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<p>Bandwidth control with different values of parameter W.</p>
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<p>Simulated and measured S11 and S21 frequency plots. (<b>a</b>) The proposed SWB BPF. (<b>b</b>) The proposed SWB BPF with dual stopbands.</p>
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41 pages, 7430 KiB  
Article
An Integrated Multi-Criteria Decision Making Model for the Assessment of Public Private Partnerships in Transportation Projects
by Eslam Mohammed Abdelkader, Tarek Zayed, Hassan El Fathali, Ghasan Alfalah, Abobakr Al-Sakkaf and Osama Moselhi
Mathematics 2023, 11(16), 3559; https://doi.org/10.3390/math11163559 - 17 Aug 2023
Cited by 11 | Viewed by 3247
Abstract
Public–private partnership (PPP) infrastructure projects have attracted attention over the past few years. In this regard, the selection of private partners is an integral decision to ensure its success. The selection process needs to identify, scrutinize, and pre-qualify potential private partners that sustain [...] Read more.
Public–private partnership (PPP) infrastructure projects have attracted attention over the past few years. In this regard, the selection of private partners is an integral decision to ensure its success. The selection process needs to identify, scrutinize, and pre-qualify potential private partners that sustain the greatest potential in delivering the designated public–private partnership projects. To this end, this research paper proposes an integrated multi-criteria decision-making (MCDM) model for the purpose of selection of the best private partners in PPP projects. The developed model (HYBD_MCDM) is conceptualized based on two tiers of multi-criteria decision making. In the first tier, the fuzzy analytical network process (FANP) is exploited to scrutinize the relative importance of the priorities of the selection criteria of private partners. In this respect, the PPP selection criteria are categorized as safety, environmental, technical, financial, political policy, and managerial. In the second tier, a set of seven multi-criteria decision-making (MCDM) algorithms is leveraged to determine the best private partners to deliver PPP projects. These algorithms comprise the combined compromise solution (CoCoSo), simple weighted sum product (WISP), measurement alternatives and ranking according to compromise solution (MARCOS), combinative distance-based assessment (CODAS), weighted aggregate sum product assessment (WASPAS), technique for order of preference by similarity to ideal solution (TOPSIS), and FANP. Thereafter, the Copeland algorithm is deployed to amalgamate the obtained rankings from the seven MCDM algorithms. Four real-world case studies are analyzed to test the implementation and applicability of the developed integrated model. The results indicate that varying levels of importance were exhibited among the managerial, political, and safety and environmental criteria based on the nature of the infrastructure projects. Additionally, the financial and technical criteria were appended as the most important criteria across the different infrastructure projects. It can be argued that the developed model can guide executives of governments to appraise their partner’s ability to achieve their strategic objectives. It also sheds light on prospective private partners’ strengths, weaknesses, and capacities in an attempt to neutralize threats and exploit opportunities offered by today’s construction business market. Full article
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<p>Framework of the developed integrated model for assessment of private partners in infrastructure projects (authors’ own work).</p>
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<p>Linguistic scales for pairwise comparisons (authors’ own work).</p>
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<p>Distribution of respondents according to job classification and experience years (authors’ own work).</p>
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<p>Sample of pairwise comparisons with respect to financial criteria (authors’ own work).</p>
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<p>Spearman’s rank correlation coefficient between the investigated MCDM models (authors’ own work).</p>
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<p>Kendall tau rank correlation coefficient between the investigated MCDM models (authors’ own work).</p>
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<p>Components of the developed automated platform (authors’ own work).</p>
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<p>Interface of the pairwise comparison entries and structure of XML backup file (authors’ own work).</p>
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<p>Interface of ranking of private partners based on ANP (authors’ own work).</p>
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<p>Sensitivity analysis of PPP selection criteria in case study I.</p>
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<p>Sensitivity analysis of PPP selection criteria in case study II.</p>
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<p>Sensitivity analysis of PPP selection criteria in case study III.</p>
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<p>Sensitivity analysis of PPP selection criteria in case study IV.</p>
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<p>Comparison of sensitivity of MCDM models based on sensitivity analysis runs.</p>
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<p>Comparison of sensitivity of MCDM models based on AADR.</p>
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16 pages, 4678 KiB  
Article
Cryptolepine Suppresses Colorectal Cancer Cell Proliferation, Stemness, and Metastatic Processes by Inhibiting WNT/β-Catenin Signaling
by Jude Tetteh Quarshie, Kwadwo Fosu, Nicholas Awuku Offei, Augustine Kojo Sobo, Osbourne Quaye and Anastasia Rosebud Aikins
Pharmaceuticals 2023, 16(7), 1026; https://doi.org/10.3390/ph16071026 - 19 Jul 2023
Cited by 2 | Viewed by 2549
Abstract
Colorectal cancer (CRC) is the third most frequent cancer and the second leading cause of cancer-related deaths globally. Evidence shows that over 90% of CRC cases are initiated by a deregulated Wingless Integrated Type-1 (WNT)/β-catenin signaling pathway. The WNT/β-catenin pathway also promotes CRC [...] Read more.
Colorectal cancer (CRC) is the third most frequent cancer and the second leading cause of cancer-related deaths globally. Evidence shows that over 90% of CRC cases are initiated by a deregulated Wingless Integrated Type-1 (WNT)/β-catenin signaling pathway. The WNT/β-catenin pathway also promotes CRC cell proliferation, stemness, and metastasis. Therefore, modulators of the WNT/β-catenin pathway may serve as promising regimens for CRC. This study investigated the effect of cryptolepine—a plant-derived compound—on the WNT/β-catenin pathway in CRC. Two CRC cell lines, COLO205 and DLD1, were treated with cryptolepine or XAV 939 (a WNT inhibitor) in the presence or absence of WNT3a (a WNT activator). Using a tetrazolium-based assay, cryptolepine was found to reduce cell viability in a dose- and time-dependent manner and was a more potent inhibitor of viability than XAV 939. RT-qPCR analyses showed that cryptolepine reverses WNT3a-induced expression of β-catenin, c-MYC, and WISP1, suggesting that cryptolepine inhibits WNT3a-mediated activation of WNT/β-catenin signaling. Cryptolepine also repressed WNT3a-induced OCT4 and CD133 expression and suppressed colony formation of the cells, indicating that cryptolepine inhibits the stemness of CRC cells. Additionally, cryptolepine inhibited WNT3a-induced epithelial-to-mesenchymal transition by reducing the expression of SNAI1 and TWIST1 genes. In a wound healing assay, cryptolepine was found to suppress cell migration under unstimulated and WNT3a-stimulated conditions. Moreover, cryptolepine downregulated WNT3a-induced expression of MMP2 and MMP9 genes, which are involved in cancer cell invasion. Altogether, cryptolepine suppresses CRC cell proliferation, stemness, and metastatic properties by inhibiting WNT3a-mediated activation of the WNT/β-catenin signaling pathway. These findings provide a rationale for considering cryptolepine as a potential WNT inhibitor in CRC. Full article
(This article belongs to the Special Issue Targeting the β-Catenin/Wnt Signaling for Cancer Therapy)
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Figure 1

Figure 1
<p>Effects of cryptolepine, XAV 939, and WNT3a on cell viability. COLO205 and DLD1 cells were treated with increasing concentrations of (<b>A</b>) cryptolepine or (<b>B</b>) XAV 939 for 24, 48, and 72 h, or (<b>C</b>) WNT3a for 24 h. Cell viability was determined using an MTT assay. Data are presented as mean ± SEM of three independent experiments performed in triplicate. * <span class="html-italic">p</span> ≤ 0.05, ** <span class="html-italic">p</span> ≤ 0.01, *** <span class="html-italic">p</span> ≤ 0.001, **** <span class="html-italic">p</span> ≤ 0.0001 vs. untreated. ns: not significant.</p>
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<p>Cryptolepine inhibits WNT/β-catenin signaling in CRC cells. COLO205 and DLD1 cells were treated with cryptolepine or XAV 939 for 48 h in the presence or absence of WNT3a. The mRNA levels of (<b>A</b>) <span class="html-italic">β-catenin</span>, (<b>B</b>) <span class="html-italic">c-MYC</span>, and (<b>C</b>) <span class="html-italic">WISP1</span> were determined by RT-qPCR. Data are presented as mean ± SEM of three independent experiments performed in triplicate. ** <span class="html-italic">p</span> ≤ 0.01, *** <span class="html-italic">p</span> ≤ 0.001, **** <span class="html-italic">p</span> ≤ 0.0001 vs. untreated. # <span class="html-italic">p</span> ≤ 0.05, ## <span class="html-italic">p</span> ≤ 0.01, ### <span class="html-italic">p</span> ≤ 0.001, #### <span class="html-italic">p</span> ≤ 0.0001 vs. WNT3a. CRYP: cryptolepine; XAV: XAV 939; mRNA: messenger ribonucleic acid; ns: not significant.</p>
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<p>Cryptolepine downregulates stem cell markers in CRC. COLO205 and DLD1 cells were treated with cryptolepine or XAV 939 for 48 h in the presence or absence of WNT3a. The mRNA levels of (<b>A</b>) <span class="html-italic">OCT4</span> and (<b>B</b>) <span class="html-italic">CD133</span> were determined by RT-qPCR. Data are presented as mean ± SEM of three independent experiments performed in triplicate. ** <span class="html-italic">p</span> ≤ 0.01, *** <span class="html-italic">p</span> ≤ 0.001, **** <span class="html-italic">p</span> ≤ 0.0001 vs. untreated. ## <span class="html-italic">p</span> ≤ 0.01, ### <span class="html-italic">p</span> ≤ 0.001, #### <span class="html-italic">p</span> ≤ 0.0001 vs. WNT3a. CRYP: cryptolepine; XAV: XAV 939; mRNA: messenger ribonucleic acid; ns: not significant.</p>
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<p>Cryptolepine inhibits clonogenicity in CRC. (<b>A</b>) COLO205 and (<b>B</b>) DLD1 cells were treated with cryptolepine or XAV 939 in the presence or absence of WNT3a, and a colony formation assay was performed. Colony areas are expressed as a percentage of untreated cells and presented as bar charts. Data are presented as mean ± SEM of three independent experiments performed in triplicate. *** <span class="html-italic">p</span> ≤ 0.001, **** <span class="html-italic">p</span> ≤ 0.0001 vs. untreated. ## <span class="html-italic">p</span> ≤ 0.01, #### <span class="html-italic">p</span> ≤ 0.0001 vs. WNT3a. CRYP: cryptolepine; XAV: XAV 939.</p>
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<p>Cryptolepine represses epithelial-to-mesenchymal transition (EMT) in CRC. COLO205 and DLD1 cells were treated with cryptolepine or XAV 939 for 48 h in the presence or absence of WNT3a. The mRNA levels of (<b>A</b>) <span class="html-italic">SNAI1</span> and (<b>B</b>) <span class="html-italic">TWIST1</span> were determined by RT-qPCR. Data are presented as mean ± SEM of three independent experiments performed in triplicate. **** <span class="html-italic">p</span> ≤ 0.0001 vs. untreated. ## <span class="html-italic">p</span> ≤ 0.01, #### <span class="html-italic">p</span> ≤ 0.0001 vs. WNT3a. CRYP: cryptolepine; XAV: XAV 939; mRNA: messenger ribonucleic acid; ns: not significant.</p>
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<p>Cryptolepine reduces CRC cell migration. DLD1 cells were treated with cryptolepine or XAV 939 for 48 h in the (<b>A</b>) presence or (<b>B</b>) absence of WNT3a. The wound area at each time point is expressed as a percentage of the 0 h. Original magnification ×100. Data are presented as mean ± SEM of three independent experiments performed in triplicate. ** <span class="html-italic">p</span> ≤ 0.01, **** <span class="html-italic">p</span> ≤ 0.0001 vs. untreated. ### <span class="html-italic">p</span> ≤ 0.001, #### <span class="html-italic">p</span> ≤ 0.0001 vs. WNT3a. CRYP: cryptolepine; XAV: XAV 939.</p>
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<p>Cryptolepine reduces CRC cell invasiveness. COLO205 and DLD1 cells were treated with cryptolepine or XAV 939 for 48 h in the presence or absence of WNT3a. The mRNA levels of (<b>A</b>) <span class="html-italic">MMP2</span> and (<b>B</b>) <span class="html-italic">MMP9</span> were determined by RT-qPCR. Data are presented as mean ± SEM of three independent experiments performed in triplicate. * <span class="html-italic">p</span> ≤ 0.05, ** <span class="html-italic">p</span> ≤ 0.01, **** <span class="html-italic">p</span> ≤ 0.0001 vs. untreated. ## <span class="html-italic">p</span> ≤ 0.01, ### <span class="html-italic">p</span> ≤ 0.001, #### <span class="html-italic">p</span> ≤ 0.0001 vs. WNT3a. CRYP: cryptolepine; XAV: XAV 939; mRNA: messenger ribonucleic acid; ns: not significant.</p>
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<p>Proposed mechanism through which cryptolepine inhibits CRC progression via WNT/β-catenin signaling. WNT3a interacts with its cognate receptor to trigger a series of intracellular events that culminate in the upregulation of WNT target genes. Cryptolepine downregulates the WNT target genes in CRC cells, resulting in the inhibition of proliferation, stemness, and metastasis.</p>
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Article
Identification of Novel Diagnostic and Prognostic Gene Signature Biomarkers for Breast Cancer Using Artificial Intelligence and Machine Learning Assisted Transcriptomics Analysis
by Zeenat Mirza, Md Shahid Ansari, Md Shahid Iqbal, Nesar Ahmad, Nofe Alganmi, Haneen Banjar, Mohammed H. Al-Qahtani and Sajjad Karim
Cancers 2023, 15(12), 3237; https://doi.org/10.3390/cancers15123237 - 18 Jun 2023
Cited by 13 | Viewed by 5273
Abstract
Background: Breast cancer (BC) is one of the most common female cancers. Clinical and histopathological information is collectively used for diagnosis, but is often not precise. We applied machine learning (ML) methods to identify the valuable gene signature model based on differentially expressed [...] Read more.
Background: Breast cancer (BC) is one of the most common female cancers. Clinical and histopathological information is collectively used for diagnosis, but is often not precise. We applied machine learning (ML) methods to identify the valuable gene signature model based on differentially expressed genes (DEGs) for BC diagnosis and prognosis. Methods: A cohort of 701 samples from 11 GEO BC microarray datasets was used for the identification of significant DEGs. Seven ML methods, including RFECV-LR, RFECV-SVM, LR-L1, SVC-L1, RF, and Extra-Trees were applied for gene reduction and the construction of a diagnostic model for cancer classification. Kaplan–Meier survival analysis was performed for prognostic signature construction. The potential biomarkers were confirmed via qRT-PCR and validated by another set of ML methods including GBDT, XGBoost, AdaBoost, KNN, and MLP. Results: We identified 355 DEGs and predicted BC-associated pathways, including kinetochore metaphase signaling, PTEN, senescence, and phagosome-formation pathways. A hub of 28 DEGs and a novel diagnostic nine-gene signature (COL10A, S100P, ADAMTS5, WISP1, COMP, CXCL10, LYVE1, COL11A1, and INHBA) were identified using stringent filter conditions. Similarly, a novel prognostic model consisting of eight-gene signatures (CCNE2, NUSAP1, TPX2, S100P, ITM2A, LIFR, TNXA, and ZBTB16) was also identified using disease-free survival and overall survival analysis. Gene signatures were validated by another set of ML methods. Finally, qRT-PCR results confirmed the expression of the identified gene signatures in BC. Conclusion: The ML approach helped construct novel diagnostic and prognostic models based on the expression profiling of BC. The identified nine-gene signature and eight-gene signatures showed excellent potential in BC diagnosis and prognosis, respectively. Full article
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Figure 1
<p>Boxplot showing the expression distribution for dataset GSE7904. (<b>A</b>) Raw (un-normalized) expression distribution with log2 scale in the range of −200 to 400. (<b>B</b>) Normalized intensities showing almost similar distributions of expression intensities, with the log2 scale in the range of 0 to 12.</p>
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<p>Volcano plot showing differentially expressed genes: (i) the majority were non-significant (black), (ii) upregulated DEGs (red), and (iii) downregulated DEGs (blue).</p>
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<p>Canonical pathways derived using the IPA tool. (<b>A</b>) Kinetochore metaphase signaling pathway, (<b>B</b>) PTEN pathway overlapped with breast cancer associated genes.</p>
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<p>(<b>A</b>) Venn diagram showing 28 hub genes derived from the intersection of DEGs &gt; 3 ML and DEGs &gt; 4 datasets. (<b>B</b>) Unsupervised hierarchical clustering: heatmap of 701 samples, including 356 breast tumor (BT, cyan) and 345 normal breast (NB, pink) tissues, showing the gene expression pattern of 28 hub genes, including diagnostic and prognostic gene signatures. Upregulated genes are shown in red and downregulated genes are in blue.</p>
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<p>K-nearest neighbors (KNN)-based ML model for diagnostic gene signature showing the mean ROC (AUC 0.989 ± 0.013).</p>
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<p>PCA plot showing an overall distribution of the samples (n = 701), including breast tumor (blue) and normal breast tissue (red) based on transcriptomics profiles: (<b>A</b>) 54,675 probes, (<b>B</b>) 355 DEGs, (<b>C</b>) 28 hub genes, and (<b>D</b>) diagnostic nine-gene signature.</p>
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<p>KM plot based on the relapse-free survival analysis of eight individual genes (mRNA, gene-chip) of prognostic gene signature. The <span class="html-italic">X</span>-axis and <span class="html-italic">Y</span>-axis represent time in months and the probability of the survival of patients, respectively. The impact of the high and low expression of the gene on patient survival is shown in red and black lines, respectively.</p>
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<p>KM plot based on the overall survival analysis of eight individual genes (mRNA, gene-chip) of prognostic gene signature. The <span class="html-italic">X</span>-axis and <span class="html-italic">Y</span>-axis represent time in months and the probability of the survival of patients, respectively. The impact of the high and low expression of the gene on patient survival is shown in red and black lines, respectively.</p>
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<p>RFS and OS analyses and the validation of upregulated (<span class="html-italic">CCNE2, NUSAP1, TPX2</span>, and <span class="html-italic">S100P</span>), and downregulated (<span class="html-italic">ITM2A, LIFR, TNXA,</span> and <span class="html-italic">ZBTB16</span>) gene groups (mRNA, RNA seq) of the prognostic gene signature. The <span class="html-italic">X</span>-axis and <span class="html-italic">Y</span>-axis represent time in months and the probability of the survival of patients. The impact of the high and low expression of the gene on patient survival is shown in red and black lines, respectively.</p>
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<p>Gradient-boosting decision trees (GBDT) based on the ML model for the prognostic gene signature showing the mean ROC (AUC 0.993 ± 0.006).</p>
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<p>qRT-PCR results showing overexpression of <span class="html-italic">COL10A</span>, <span class="html-italic">S100P</span>, <span class="html-italic">WISP1</span>, <span class="html-italic">COMP</span>, <span class="html-italic">CXCL10</span>, <span class="html-italic">COL11A1</span>, <span class="html-italic">INHBA</span>; <span class="html-italic">CCNE2</span>, <span class="html-italic">NUSAP1</span>, <span class="html-italic">TPX2</span>, and <span class="html-italic">S100P</span> genes, and under-expression of <span class="html-italic">ADAMTS5</span>, <span class="html-italic">LYVE1</span>, <span class="html-italic">ITM2A</span>, <span class="html-italic">LIFR</span>, <span class="html-italic">TNXA</span>, and <span class="html-italic">ZBTB16</span> genes.</p>
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