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Search Results (1,644)

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17 pages, 668 KiB  
Article
Impact of Nanoparticle Addition and Ozone Pre-Treatment on Mesophilic Methanogenesis in Temperature-Phased Anaerobic Digestion
by Encarnación Díaz Domínguez, María Eugenia Ibañez López, Jacek Mąkinia, Francisco Jesús Fernández-Morales and José Luis García Morales
Appl. Sci. 2024, 14(20), 9504; https://doi.org/10.3390/app14209504 (registering DOI) - 17 Oct 2024
Abstract
Biodegradable organic waste offers significant opportunities for resource recovery within the frame of the circular economy. In this work, the effects of carbon-encapsulated iron nanoparticles and ozone pre-treatments in the mesophilic methanogenic stage of a temperature-phased an-aerobic digestion have been studied using biochemical [...] Read more.
Biodegradable organic waste offers significant opportunities for resource recovery within the frame of the circular economy. In this work, the effects of carbon-encapsulated iron nanoparticles and ozone pre-treatments in the mesophilic methanogenic stage of a temperature-phased an-aerobic digestion have been studied using biochemical methanogenic potential (BMP) tests and modeling simulation. To do that, digestates from a pre-treated thermophilic acidogenic reactor that co-digested sludge and wine vinasse were used. The addition of nanoparticles favored the removal of particulate matter, which increased by 9% and 6% in terms of total solids and volatile solids, respectively. When combined with ozone pre-treatment, these increases were 27% and 24%, respectively, demonstrating enhanced AD efficiency. The dose of iron nanoparticles encapsulated in carbon did not result in a statistically significant increase in methane production when sludge and vinasse were used as feedstock. The combination of nanoparticles with the ozone pre-treatment significantly improved the methanogenic phase of the second stage, increasing the methane production yield by 22% and reducing the lag phase from 10 days to 3 days, according to the modified Gompertz model. Full article
5 pages, 642 KiB  
Proceeding Paper
Optimal Location of Best Management Practices for Flood Mitigation in Urban Drainage Systems
by Enrico Creaco, Arianna Dada, Giovanna Grossi and Sara Todeschini
Eng. Proc. 2024, 69(1), 189; https://doi.org/10.3390/engproc2024069189 - 14 Oct 2024
Viewed by 43
Abstract
The present work presents a bi-objective optimization methodology, which is aimed at simultaneously minimizing the total installation costs of management systems as well as urban flooding, as a tool to be conveniently adopted as part of a decision support system to help identify [...] Read more.
The present work presents a bi-objective optimization methodology, which is aimed at simultaneously minimizing the total installation costs of management systems as well as urban flooding, as a tool to be conveniently adopted as part of a decision support system to help identify the optimal location of best management practices (BMPs). For each sub-catchment present in an urban drainage system, the decision variables include the rate of impervious areas to be used for BMP installation. The performance of the urban drainage system following optimal BMP installation is tested against climate change scenarios obtained from a real case study conducted in the industrial area of Brescia; the numerical model of this study can be obtained via the EPASWMM software. Full article
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<p>Case study network (<b>a</b>) and Chicago hyetograph (<b>b</b>) used in EPASWMM.</p>
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<p>Pareto front of optimal solutions in the trade-off between costs and flooding volume.</p>
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30 pages, 1907 KiB  
Review
Molecular Signaling Pathways and MicroRNAs in Bone Remodeling: A Narrative Review
by Monica Singh, Puneetpal Singh, Baani Singh, Kirti Sharma, Nitin Kumar, Deepinder Singh and Sarabjit Mastana
Diseases 2024, 12(10), 252; https://doi.org/10.3390/diseases12100252 - 12 Oct 2024
Viewed by 383
Abstract
Bone remodeling is an intricate process executed throughout one’s whole life via the cross-talk of several cellular events, progenitor cells and signaling pathways. It is an imperative mechanism for regaining bone loss, recovering damaged tissue and repairing fractures. To achieve this, molecular signaling [...] Read more.
Bone remodeling is an intricate process executed throughout one’s whole life via the cross-talk of several cellular events, progenitor cells and signaling pathways. It is an imperative mechanism for regaining bone loss, recovering damaged tissue and repairing fractures. To achieve this, molecular signaling pathways play a central role in regulating pathological and causal mechanisms in different diseases. Similarly, microRNAs (miRNAs) have shown promising results in disease management by mediating mRNA targeted gene expression and post-transcriptional gene function. However, the role and relevance of these miRNAs in signaling processes, which regulate the delicate balance between bone formation and bone resorption, are unclear. This review aims to summarize current knowledge of bone remodeling from two perspectives: firstly, we outline the modus operandi of five major molecular signaling pathways, i.e.,the receptor activator of nuclear factor kappa-B (RANK)-osteoprotegrin (OPG) and RANK ligand (RANK-OPG-RANKL), macrophage colony-stimulating factor (M-CSF), Wnt/β-catenin, Jagged/Notch and bone morphogenetic protein (BMP) pathways in regards to bone cell formation and function; and secondly, the miRNAs that participate in these pathways are introduced. Probing the miRNA-mediated regulation of these pathways may help in preparing the foundation for developing targeted strategies in bone remodeling, repair and regeneration. Full article
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<p>The figure shows (a) Wnt signaling in which mesenchymal stem cells are differentiated into osteoblast precursor cells and transformed to osteoblasts. Prompted by Wnt proteins, these transformations are induced however by the inhibition of TNFα-directed DKK-1 and the drug Macitentan. (b) RANK-RANKL-OPG signaling in which hematopoietic stem cells are differentiated into osteoclast precursor cells, transforming them into osteoclasts. This transformation is stimulated by RANKL but inhibited by OPG, both of which are secreted by osteoblasts. (c) M-CSF signaling in which osteoclast precursor cells are transformed into osteoclasts and this transformation is augmented by M-CSF, which is secreted by osteoblasts.</p>
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<p>The figure shows the process of osteoclastogenesis and osteoblast differentiation by miRNAs through interaction of different signaling pathways.</p>
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<p>The figure illustrates Notch/Jagged signaling in which mesenchymal stem cells are differentiated into osteoblasts and are transformed into osteocytes through mineralization. Notch activation plays a dual role in this transformation by inducing it but also halting it by targeting Wnt/β-catenin pathway. On the other hand, macrophage precursors are differentiated into osteoclasts that are transformed into osteocytes.Here, notch activation also plays a dual role by inciting it either through its Notch2/Dll1 complex or by providing Notch1/Notch1–3-deficient conditions in precursor cells, which affect RANKL/OPG and M-CSF signaling. However, it is inhibited by either knocking RANK or pumping M-CSF signaling or through its Notch1/Jagged1 complex. When activating Wnt/β-catenin pathway by suppressing SOST and DKK1, this transformation is inhibited.</p>
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<p>The figure depicts TGFβ/BMP signaling in whichSMAD-dependent pathway is initiated by binding of TGFβ ligand with TGFβ receptors R1 and R2 and BMP ligand with Type I/II receptor. This is followed by phosphorylation of R-Smad 2 and 3 and R-Smad 1,5 and 8 and the complexing of Co-Smad 4 with both molecules to form the activated quaternary complex, which modulates gene expression, affecting bone remodeling. Meanwhile, in the non-canonical pathway, the same ligand–receptor binding activates other signaling molecules, such as ERK-MAPK, PI3K, JNK, p38 and Cd42, by phosphorylating them. These activated molecules then alter expression of various bone-related genes.</p>
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15 pages, 3023 KiB  
Article
Developmental and Molecular Effects of C-Type Natriuretic Peptide Supplementation in In Vitro Culture of Bovine Embryos
by Camila Bortoliero Costa, Nathália Covre da Silva, Amanda Nespolo Silva, Elisa Mariano Pioltine, Thaisy Tino Dellaqua, Amanda Fonseca Zangirolamo, Flávio Vieira Meirelles, Marcelo Marcondes Seneda and Marcelo Fábio Gouveia Nogueira
Int. J. Mol. Sci. 2024, 25(20), 10938; https://doi.org/10.3390/ijms252010938 - 11 Oct 2024
Viewed by 272
Abstract
The use of C-type natriuretic peptide (CNP) in the interaction with the oocyte and in the temporary postponement of spontaneous meiosis resumption has already been well described. However, its action in pre-implantation developmental-stage embryos is yet to be understood. Thus, our study aimed [...] Read more.
The use of C-type natriuretic peptide (CNP) in the interaction with the oocyte and in the temporary postponement of spontaneous meiosis resumption has already been well described. However, its action in pre-implantation developmental-stage embryos is yet to be understood. Thus, our study aimed to detect the presence of the canonical CNP receptor (natriuretic peptide receptor, NPR2) in germinal vesicle (GV)-, metaphase II (MII)-, presumptive zygote (PZ)-, morula (MO)-, and blastocyst (BL)-stage embryos and, later, to observe possible modulations on the embryos when co-cultured with CNP. In Experiment I, we detected and quantified NPR2 on the abovementioned embryo stages. Further, in Experiment II, we intended to test different concentrations (100, 200, or 400 nM of CNP) at different times of inclusion in the in vitro culture (IVC; inclusion from the beginning, i.e., day 1, or from day 5). In Experiment III, 400 nM of CNP was used on day 1 (D1) in the IVC, which was not demonstrated to be embryotoxic, and it showed potentially promising results in the blastocyst production rate when compared to the control. Thus, we analyzed the embryonic development rates of bovine embryos (D7) and hatching kinetics (D7, D8, and D9). Subsequently, morula and blastocyst were collected and evaluated for transcript abundance of their competence and quality (apoptosis, oxidative stress, proliferation, and differentiation) and lipid metabolism. Differences with probabilities less than p < 0.05, and/or fold change (FC) > 1.5, were considered significant. We demonstrate the presence of NPR2 until the blastocyst development stage, when there was a significant decrease in membrane receptors. There was no statistical difference in the production rate after co-culture with 400 nM CNP. However, when we evaluated the abundance of morula transcripts, there was an upregulated transcription in ADCY6 (p = 0.057) and downregulated transcripts in BMP15 (p = 0.013), ACAT1 (p = 0.040), and CASP3 (p = 0.082). In addition, there was a total of 12 transcriptions in morula that presented variation FC > 1.5. In blastocysts, the treatment with CNP induced upregulation in BID, CASP3, SOX2, and HSPA5 transcripts and downregulation in BDNF, NLRP5, ELOVL1, ELOVL4, IGFBP4, and FDX1 transcripts (FC > 1.5). Thus, our study identified and quantified the presence of NPR2 in bovine pre-implantation embryos. Furthermore, 400 nM of CNP in IVC, a concentration not previously described in the literature, modulated some transcripts related to embryonic metabolism, and this was not embryotoxic morphologically. Full article
(This article belongs to the Special Issue Molecular Research on Embryo Developmental Potential)
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<p>NPR2 localization in bovine oocytes and pre-implantation-stage embryos. The green color indicates NPR2 staining, and the blue color indicates nuclear staining (DAPI). NPR2 protein was expressed in bovine oocytes and embryos at all stages. GV, germinal vesicle; M II, metaphase II; PZs, presumptive zygotes; Morula, morula stage; Blastocyst, blastocyst stage. Bar = 50 µm.</p>
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<p>Box plot of fluorescence intensity of NPR2 in oocytes and pre-implantation-stage embryos. Results are presented as the median and 1° and 3° interquartile intervals of five replicates/stage using 8 structures in total. Different letters above each box represent significant differences (<span class="html-italic">p</span> ≤ 0.05). GV, germinal vesicle; M II, metaphase II; PZs, presumptive zygotes; Morula, morula stage; Blastocyst, blastocyst stage. AU, arbitrary units.</p>
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<p>Effect of CNP treatment in IVC on differential gene expression in morula. Data represent the fold change in relative target abundance related to the reference gene. Downregulated transcription <span class="html-italic">ACAT1</span> (<span class="html-italic">p</span> = 0.040), <span class="html-italic">CASP3</span> (<span class="html-italic">p</span> = 0.082), and <span class="html-italic">BMP15</span> (<span class="html-italic">p</span> = 0.013) and upregulated transcription <span class="html-italic">ADCY6</span> (<span class="html-italic">p</span> = 0.057) with the addition of CNP (400 nM) on the D1 of the culture. Results are represented by least squares means ± SEM of four replicates/group. Different letters above each bar represent significant differences (<span class="html-italic">p</span> ≤ 0.08). Control (no treatment) and C-400 (400 nM of CNP).</p>
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<p>Multivariate analysis plots of the abundance of transcripts derived from untreated (control) and CNP-treated morula. (<b>A</b>) Cluster analysis heatmap showing transcriptional profiles abundance in only 12 genes most impacted from morula treated with 400 nM CNP and the control group. (<b>B</b>) Two-dimensional PLS-DA discrimination score plot between groups (5 morulas/group in 4 replicates).</p>
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<p>Multivariate analysis plots of the abundance of transcripts derived from untreated (control) and CNP-treated blastocyst. (<b>A</b>) Cluster analysis heatmap showing transcriptional profiles abundance in only 11 genes most impacted from blastocyst treated with 400 nM CNP and the control group. (<b>B</b>) Two-dimensional PLS-DA discrimination score plot between groups (3 embryos/group in 4 replicates).</p>
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<p>Illustrative experimental design. IVC, in vitro culture; EXP, experiment; GV, germinal vesicle; MII, metaphase II; PZs, presumptive zygotes; MO, morula; BL, blastocyst; CTL, control group; CNP, group treated with C-type natriuretic peptide. © 2024 BioRender.</p>
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32 pages, 2414 KiB  
Review
Pulmonary Hypertension: Pharmacological and Non-Pharmacological Therapies
by Jason Tsai, Shaista Malik and Stephanie C. Tjen-A-Looi
Life 2024, 14(10), 1265; https://doi.org/10.3390/life14101265 - 4 Oct 2024
Viewed by 707
Abstract
Pulmonary hypertension (PH) is a severe and chronic disease characterized by increased pulmonary vascular resistance and remodeling, often precipitating right-sided heart dysfunction and death. Although the condition is progressive and incurable, current therapies for the disease focus on multiple different drugs and general [...] Read more.
Pulmonary hypertension (PH) is a severe and chronic disease characterized by increased pulmonary vascular resistance and remodeling, often precipitating right-sided heart dysfunction and death. Although the condition is progressive and incurable, current therapies for the disease focus on multiple different drugs and general supportive therapies to manage symptoms and prolong survival, ranging from medications more specific to pulmonary arterial hypertension (PAH) to exercise training. Moreover, there are multiple studies exploring novel experimental drugs and therapies including unique neurostimulation, to help better manage the disease. Here, we provide a narrative review focusing on current PH treatments that target multiple underlying biochemical mechanisms, including imbalances in vasoconstrictor–vasodilator and autonomic nervous system function, inflammation, and bone morphogenic protein (BMP) signaling. We also focus on the potential of novel therapies for managing PH, focusing on multiple types of neurostimulation including acupuncture. Lastly, we also touch upon the disease’s different subgroups, clinical presentations and prognosis, diagnostics, demographics, and cost. Full article
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<p>Tools used for pulmonary hypertension (PH) diagnosis and classification. Right heart catheterization is uniquely colored because it is required for the diagnosis of PH. Tools such as exercise testing or vasoreactivity testing can be utilized when performing right heart catheterization. This figure is only a summary: it does not include all the parameters that can be measured through diagnostic tools (e.g., chest radiography can also measure factors such as right atrial dilation) nor novel diagnostics currently being explored but not yet established (e.g., serum uric acid). mPAP = mean pulmonary arterial pressure, PAWP = pulmonary arterial wedge pressure, PVR = pulmonary vascular resistance, CO = cardiac output, SvO<sub>2</sub> = mixed venous oxygen saturation, CTEPH = chronic thrombo-embolic PH, BNP = brain natriuretic peptide, NT-proBNP = N-terminal prohormone of BNP, TRVmax = maximum peak tricuspid regurgitation velocity, sPAP/PASP = pulmonary arterial systolic pressure, TAPSE = tricuspid annular plane systolic excursion, RVOT = right ventricular outflow tract, PaO<sub>2</sub>/PaCO<sub>2</sub> = partial pressure of oxygen/carbon dioxide.</p>
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<p>Potential mechanisms of acupuncture-mediated neurostimulation for pulmonary hypertension (PH).</p>
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23 pages, 1933 KiB  
Review
Timing and Graded BMP Signalling Determines Fate of Neural Crest and Ectodermal Placode Derivatives from Pluripotent Stem Cells
by Keshi Chung, Malvina Millet, Ludivine Rouillon and Azel Zine
Biomedicines 2024, 12(10), 2262; https://doi.org/10.3390/biomedicines12102262 - 4 Oct 2024
Viewed by 441
Abstract
Pluripotent stem cells (PSCs) offer many potential research and clinical benefits due to their ability to differentiate into nearly every cell type in the body. They are often used as model systems to study early stages of ontogenesis to better understand key developmental [...] Read more.
Pluripotent stem cells (PSCs) offer many potential research and clinical benefits due to their ability to differentiate into nearly every cell type in the body. They are often used as model systems to study early stages of ontogenesis to better understand key developmental pathways, as well as for drug screening. However, in order to fully realise the potential of PSCs and their translational applications, a deeper understanding of developmental pathways, especially in humans, is required. Several signalling molecules play important roles during development and are required for proper differentiation of PSCs. The concentration and timing of signal activation are important, with perturbations resulting in improper development and/or pathology. Bone morphogenetic proteins (BMPs) are one such key group of signalling molecules involved in the specification and differentiation of various cell types and tissues in the human body, including those related to tooth and otic development. In this review, we describe the role of BMP signalling and its regulation, the consequences of BMP dysregulation in disease and differentiation, and how PSCs can be used to investigate the effects of BMP modulation during development, mainly focusing on otic development. Finally, we emphasise the unique role of BMP4 in otic specification and how refined understanding of controlling its regulation could lead to the generation of more robust and reproducible human PSC-derived otic organoids for research and translational applications. Full article
(This article belongs to the Special Issue Pluripotent Stem Cell: Current Understanding and Future Directions)
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<p>Effects of BMP concentration on fate of ectodermal cells to induce epidermal, placodal, neural crest, and neural derivatives. Exposure of pluripotent stem cells to different concentrations of BMP4 results in differentiation towards different cell fates via activation of various downstream genes. High concentration of BMP4 results in activation of genes such as <span class="html-italic">K18</span>, which causes cells to differentiate towards epidermal fate. Medium concentration of BMP4, which can be due to the presence of some inhibitors such as Noggin, causes activation of <span class="html-italic">SIX1</span> for differentiation towards pre-placodal ectoderm and subsequent placodal lineages including lens, olfactory, and otic placodes. However, in the presence of WNT, neural crest fate is induced. Activation of genes such as <span class="html-italic">Hes1</span> can have an inhibitory effect on this pathway. Low concentration of BMP4, which can be the result of high levels of Noggin due to Shh signalling or the presence of Chordin, results in activation of <span class="html-italic">PAX6</span>, <span class="html-italic">NCAD</span>, and other genes that result in neural fate. (Generated using <a href="http://Biorender.com" target="_blank">Biorender.com</a>, accessed 6 September 2024).</p>
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<p>Overview of BMP signalling pathway and modulators during development of pre-placodal ectoderm. BMPs such as BMP4 bind to their receptors BMPR1A, BMPR1B, and BMPR2 on the cell surface, resulting in activation of SMADs which translocate to the nucleus to influence transcription of genes directing cell fate towards non-neural ectoderm/pre-placodal and subsequent placodal fates, and inhibiting differentiation towards neural fate. The presence of antagonists and modulators such as Noggin, Follistatin, Chordin, Gremlin, and TWSG1 alter the level of BMP activity on the cell and hence can also influence cell fate. (Generated using <a href="http://Biorender.com" target="_blank">Biorender.com</a>, accessed 6 September 2024).</p>
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21 pages, 18608 KiB  
Article
Distribution of Immunomodulation, Protection and Regeneration Factors in Cleft-Affected Bone and Cartilage
by Mārtiņš Vaivads and Māra Pilmane
Diagnostics 2024, 14(19), 2217; https://doi.org/10.3390/diagnostics14192217 - 4 Oct 2024
Viewed by 449
Abstract
Background: Craniofacial clefts can form a significant defect within bone and cartilage, which can negatively affect tissue homeostasis and the remodeling process. Multiple proteins can affect supportive tissue growth, while also regulating local immune response and tissue protection. Some of these factors, like [...] Read more.
Background: Craniofacial clefts can form a significant defect within bone and cartilage, which can negatively affect tissue homeostasis and the remodeling process. Multiple proteins can affect supportive tissue growth, while also regulating local immune response and tissue protection. Some of these factors, like galectin-10 (Gal-10), nuclear factor kappa-light-chain-enhancer of activated B cells protein 65 (NF-κB p65), heat shock protein 60 (HSP60) and 70 (HSP70) and cathelicidin (LL-37), have not been well studied in cleft-affected supportive tissue, while more known tissue regeneration regulators like type I collagen (Col-I) and bone morphogenetic proteins 2 and 4 (BMP-2/4) have not been assessed jointly with immunomodulation and protective proteins. Information about the presence and interaction of these proteins in cleft-affected supportive tissue could be helpful in developing biomaterials and improving cleft treatment. Methods: Two control groups and two cleft patient groups for bone tissue and cartilage, respectively, were organized with five patients in each group. Immunohistochemistry with the semiquantitative counting method was implemented to determine Gal-10-, NF-κB p65-, HSP60-, HSP70-, LL-37-, Col-I- and BMP-2/4-positive cells within the tissue. Results: Factor-positive cells were identified in each study group. Multiple statistically significant correlations were identified. Conclusions: A significant increase in HSP70-positive chondrocytes in cleft patients could indicate that HSP70 might be reacting to stressors caused by the local tissue defect. A significant increase in Col-I-positive osteocytes in cleft patients might indicate increased bone remodeling and osteocyte activity due to the presence of a cleft. Correlations between factors indicate notable differences in molecular interactions within each group. Full article
(This article belongs to the Section Pathology and Molecular Diagnostics)
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<p>Hematoxylin and eosin (H&amp;E) stained control tissue and cleft-affected supportive tissue. (<b>A</b>) Control bone tissue, H&amp;E, 200×. (<b>B</b>) Cleft-affected bone tissue with surrounding periosteum, H&amp;E, 200×. (<b>C</b>) Control cartilage tissue with surrounding perichondrium, H&amp;E, 200×. (<b>D</b>) Cleft-affected cartilage tissue, H&amp;E, 200×.</p>
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<p>Immunohistochemistry (IMH) of galectin-10 (Gal-10)-containing cells in control and cleft-affected supportive tissue. (<b>A</b>) A few Gal-10-positive osteocytes (arrow) in control group bone tissue, Gal-10 IMH, 200×. (<b>B</b>) A few Gal-10-positive osteocytes (arrows) in cleft-affected bone tissue, Gal-10 IMH, 200×. (<b>C</b>) A few Gal-10-positive chondroblasts and chondrocytes (arrow) in the control group hyaline cartilage, Gal-10 IMH, 200×. (<b>D</b>) A rare occurrence of Gal-10-positive chondrocytes (arrows) in cleft-affected hyaline cartilage, Gal-10 IMH, 200×.</p>
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<p>Immunohistochemistry of nuclear factor kappa-light-chain-enhancer of activated B cells protein 65 (NF-κB p65)-containing cells in control and cleft-affected supportive tissue. (<b>A</b>) A few NF-κB p65-positive osteocytes (arrow) in control bone tissue, NF-κB p65 IMH, 200×. (<b>B</b>) A few NF-κB p65-positive osteocytes (arrows) in cleft-affected bone tissue, NF-κB p65 IMH, 200×. (<b>C</b>) Few to moderate number of NF-κB p65-positive chondrocytes and chondroblasts (arrows) in control hyaline cartilage, NF-κB p65 IMH, 200×. (<b>D</b>) Numerous NF-κB p65-positive chondrocytes in cleft-affected cartilage, NF-κB p65 IMH, 200×.</p>
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<p>Immunohistochemistry of heat shock protein 60 (HSP60)-containing cells in control and cleft-affected supportive tissue. (<b>A</b>) A few HSP60-positive osteocytes (arrows) in bone tissue of a control patient, HSP60 IMH, 200×. (<b>B</b>) A few HSP60-positive osteocytes (arrows) in cleft-affected bone tissue, HSP60 IMH, 200×. (<b>C</b>) Few to moderate number of HSP60-positive chondrocytes and chondroblasts (arrow) in control patient hyaline cartilage, HSP60 IMH, 200×. (<b>D</b>) Moderate to numerous HSP60-positive chondrocytes and chondroblasts in cleft-affected cartilage, HSP60 IMH, 200×.</p>
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<p>Immunohistochemistry of heat shock protein 70 (HSP70)-containing cells in control and cleft-affected supportive tissue. (<b>A</b>) Moderate number of HSP70-positive osteocytes in control bone tissue, HSP70 IMH, 200×. (<b>B</b>) A few HSP70-positive bone cells (arrow) in cleft-affected bone tissue, HSP70 IMH, 200×. (<b>C</b>) Moderate number of HSP70-positive chondrocytes in control hyaline cartilage, HSP70 IMH, 200×. (<b>D</b>) Numerous HSP70-positive chondrocytes in cleft-affected cartilage, HSP70 IMH, 200×.</p>
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<p>Immunohistochemistry of cathelicidin (LL-37)-containing cells in control and cleft-affected supportive tissue. (<b>A</b>) A few LL-37-positive osteocytes (arrows) in control bone tissue, LL-37 IMH, 200×. (<b>B</b>) Few to moderate number of LL-37-positive osteocytes (arrows) in cleft-affected bone tissue, LL-37 IMH, 200×. (<b>C</b>) A few LL-37-positive chondrocytes (arrow) in control cartilage tissue, LL-37 IMH, 200×. (<b>D</b>) Moderate number of LL-37-positive chondrocytes (arrows) in cleft-affected cartilage, LL-37 IMH, 200×.</p>
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<p>Immunohistochemistry of type I collagen (Col-I)-containing cells in control and cleft-affected supportive tissue. (<b>A</b>) A rare occurrence of Col-I-positive osteocytes (arrows) in control bone tissue, Col-I IMH, 200×. (<b>B</b>) A few Col-I-positive osteocytes (arrows) in cleft-affected bone tissue, Col-I IMH, 200×. (<b>C</b>) A few Col-I-positive chondrocytes (arrows) in control hyaline cartilage, Col-I IMH, 200×. (<b>D</b>) Few to moderate number of Col-I-positive chondrocytes (arrows) in cleft-affected hyaline cartilage, Col-I IMH, 200×.</p>
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<p>Immunohistochemistry of bone morphogenetic protein 2/4 (BMP-2/4)-containing cells in control and cleft-affected supportive tissue. (<b>A</b>) Moderate number of BMP-2/4-positive osteocytes in control bone tissue, BMP-2/4 IMH, 200×. (<b>B</b>) A few BMP-2/4-positive osteocytes (arrows) in cleft-affected bone tissue, BMP-2/4 IMH, 200×. (<b>C</b>) Moderate number of BMP-2/4-positive chondrocytes in control hyaline cartilage, BMP-2/4 IMH, 200×. (<b>D</b>) Numerous to abundant BMP-2/4-positive chondrocytes in cleft-affected hyaline cartilage, BMP-2/4 IMH, 200×.</p>
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23 pages, 10244 KiB  
Article
Exploring the Mechanism of Sempervirine Inhibiting Glioblastoma Invasion Based on Network Pharmacology and Bioinformatics
by Bingqiang Zhang, Wenyi Wang, Yu Song, Huixian Chen, Xinxin Lin, Jingjing Chen, Ying Chen, Jinfang Huang, Desen Li and Shuisheng Wu
Pharmaceuticals 2024, 17(10), 1318; https://doi.org/10.3390/ph17101318 - 2 Oct 2024
Viewed by 555
Abstract
Background: Invasion is an important characteristic of the malignancy of glioblastoma (GBM) and a significant prognostic factor. Sempervirine (SPV), a yohimbine-type alkaloid, has been proven to inhibit GBM cells proliferation in previous research and found to have a potential effect in anti-invasion, [...] Read more.
Background: Invasion is an important characteristic of the malignancy of glioblastoma (GBM) and a significant prognostic factor. Sempervirine (SPV), a yohimbine-type alkaloid, has been proven to inhibit GBM cells proliferation in previous research and found to have a potential effect in anti-invasion, but its mechanism of anti-invasion is still unknown. Methods: To explore its pharmacodynamics in inhibiting GBM cell invasion in this study, we combined network pharmacology and bioinformatics to comprehensive exploratory analysis of SPV and verified the mechanism in vitro. Results: Firstly, targets of SPV and invasion-related genes were collected from public databases. Moreover, GBM samples were obtained to analyze differentially expressed genes (DEGs) from The Cancer Genome Atlas (TCGA). Then, the relevant targets of SPV inhibiting GBM invasion (SIGI) were obtained through the intersection of the three gene sets. Further, GO and KEGG analysis showed that the targets of SIGI were heavily enriched in the AKT signaling pathway. Subsequently, based on the method of machine learning, a clinical prognostic model of the relevant targets of SIGI was constructed using GBM samples from TCGA and the Gene Expression Omnibus (GEO). A four-genes model (DUSP6, BMP2, MMP2, and MMP13) was successfully constructed, and Vina Scores of MMP2 and MMP13 in molecular docking were higher, which may be the main targets of SIGI. Then, the effect of SIGI was confirmed via functional experiments on invasion, migration, and adhesion assay, and the effect involved changes in the expressions of p-AKT, MMP2 and MMP13. Finally, combined with AKT activator (SC79) and inhibitor (MK2206), we further confirmed that SPV inhibits GBM invasion through AKT phosphorylation. Conclusions: This study provides valuable and an expected point of view into the regulation of AKT phosphorylation and inhibition of GBM invasion by SPV. Full article
(This article belongs to the Section Pharmacology)
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<p>Framework on basis of experimental method to research the targets of SIGI.</p>
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<p>Network pharmacology analysis of SIGI. (<b>A</b>) Molecular structure of SPV. (<b>B</b>) Volcano plot of GBM DEGs. (<b>C</b>) Venn diagram of the overlapping targets of SPV, GBM DEGs, and invasion-related genes. (<b>D</b>) The GO enrichment analysis in BP, CC, and MF related to the targets of SIGI. (<b>E</b>) The KEGG enrichment analysis of the targets of SIGI. (<b>F</b>) Compound-disease-target network of SIGI. Yellow nodes indicate the SPV, red nodes denote the 20 signaling pathways screened from the KEGG analysis, and green nodes symbolize the overlapped target of GBM DEGs, targets of SPV, and invasion-related genes.</p>
Full article ">Figure 2 Cont.
<p>Network pharmacology analysis of SIGI. (<b>A</b>) Molecular structure of SPV. (<b>B</b>) Volcano plot of GBM DEGs. (<b>C</b>) Venn diagram of the overlapping targets of SPV, GBM DEGs, and invasion-related genes. (<b>D</b>) The GO enrichment analysis in BP, CC, and MF related to the targets of SIGI. (<b>E</b>) The KEGG enrichment analysis of the targets of SIGI. (<b>F</b>) Compound-disease-target network of SIGI. Yellow nodes indicate the SPV, red nodes denote the 20 signaling pathways screened from the KEGG analysis, and green nodes symbolize the overlapped target of GBM DEGs, targets of SPV, and invasion-related genes.</p>
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<p>Construction of the prognostic model with TCGA and GEO samples. (<b>A</b>) Univariate Cox regression analysis of 76 genes with <span class="html-italic">p</span> &lt; 0.05 in TCGA_GBM database; hazard ratio (HR) represents the ratio by which a factor affects survival (HR &lt; 1: protective roles; HR &gt; 1: adverse roles; HR = 1: make no difference). (<b>B</b>) LASSO coefficient profiles of the 4 targets of SIGI with non-zero coefficients in the TCGA_GBM database; (<b>C</b>) LASSO regression with the screening of optimal parameters (lambda) obtained 4 prognostic genes. The distribution and median value of the SIGI risk score in the TCGA samples (<b>D</b>) and the GEO samples (<b>H</b>). The distributions of survival status and SIGI risk scores in the TCGA samples (<b>E</b>) and the GEO samples (<b>I</b>). The AUC of time-dependent ROC curves of the TCGA samples (<b>F</b>) and the GEO samples (<b>J</b>). The Kaplan–Meier curves of the TCGA samples (<b>G</b>) and the GEO samples (<b>K</b>).</p>
Full article ">Figure 3 Cont.
<p>Construction of the prognostic model with TCGA and GEO samples. (<b>A</b>) Univariate Cox regression analysis of 76 genes with <span class="html-italic">p</span> &lt; 0.05 in TCGA_GBM database; hazard ratio (HR) represents the ratio by which a factor affects survival (HR &lt; 1: protective roles; HR &gt; 1: adverse roles; HR = 1: make no difference). (<b>B</b>) LASSO coefficient profiles of the 4 targets of SIGI with non-zero coefficients in the TCGA_GBM database; (<b>C</b>) LASSO regression with the screening of optimal parameters (lambda) obtained 4 prognostic genes. The distribution and median value of the SIGI risk score in the TCGA samples (<b>D</b>) and the GEO samples (<b>H</b>). The distributions of survival status and SIGI risk scores in the TCGA samples (<b>E</b>) and the GEO samples (<b>I</b>). The AUC of time-dependent ROC curves of the TCGA samples (<b>F</b>) and the GEO samples (<b>J</b>). The Kaplan–Meier curves of the TCGA samples (<b>G</b>) and the GEO samples (<b>K</b>).</p>
Full article ">Figure 3 Cont.
<p>Construction of the prognostic model with TCGA and GEO samples. (<b>A</b>) Univariate Cox regression analysis of 76 genes with <span class="html-italic">p</span> &lt; 0.05 in TCGA_GBM database; hazard ratio (HR) represents the ratio by which a factor affects survival (HR &lt; 1: protective roles; HR &gt; 1: adverse roles; HR = 1: make no difference). (<b>B</b>) LASSO coefficient profiles of the 4 targets of SIGI with non-zero coefficients in the TCGA_GBM database; (<b>C</b>) LASSO regression with the screening of optimal parameters (lambda) obtained 4 prognostic genes. The distribution and median value of the SIGI risk score in the TCGA samples (<b>D</b>) and the GEO samples (<b>H</b>). The distributions of survival status and SIGI risk scores in the TCGA samples (<b>E</b>) and the GEO samples (<b>I</b>). The AUC of time-dependent ROC curves of the TCGA samples (<b>F</b>) and the GEO samples (<b>J</b>). The Kaplan–Meier curves of the TCGA samples (<b>G</b>) and the GEO samples (<b>K</b>).</p>
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<p>Univariate and multivariate Cox regression analyses concerning OS in the TCGA samples (<b>A</b>,<b>B</b>) and the GEO samples (<b>C</b>,<b>D</b>). Hazard ratio (HR) represents the ratio by which a factor affects survival (HR &lt; 1: protective roles; HR &gt; 1: adverse roles; HR = 1: make no difference).</p>
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<p>The results of molecular docking (<b>A</b>–<b>E</b>). The docking modes of SPV with MMP2, MMP13, DUSP6, BMP2, AKT1.</p>
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<p>The results of molecular docking (<b>A</b>–<b>E</b>). The docking modes of SPV with MMP2, MMP13, DUSP6, BMP2, AKT1.</p>
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<p>Sempervirine efficiently inhibits invasion, migration, and adhesion in U87 cells. (<b>A</b>) After SPV intervention for 48 h, cell viability was measured by CCK8 assay. (<b>B</b>,<b>E</b>) Transwell invasion assay was treated with SPV for 36 h in U87 cells. (<b>C</b>,<b>F</b>) Transwell migration assay of U87 cells was treated with SPV for 36 h. (<b>D</b>,<b>G</b>) Effect of SPV on the adhesion to Matrigel-coated plate after 1 h exposure. The cells were stained with crystal violet to be photographed (×200) and calculated using Image J (1.52i) software (n = 5). Data are presented as the Mean ± SD (n = 5). <sup>ns</sup> <span class="html-italic">p</span> &gt; 0.05, ** <span class="html-italic">p</span> &lt; 0.01 and *** <span class="html-italic">p</span> &lt; 0.001 compared with the control group.</p>
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<p>SPV regulates p-AKT, MMP2, and MMP13 expression in U87 cells. (<b>A</b>–<b>F</b>) P-AKT, MMP2, and MMP13 was measured by immunofluorescence analysis of U87 cells treated with the series concentrations of SPV for 48 h. The cells were photographed (×200) and calculated by Image J (1.52i) software (n = 5). (<b>G</b>–<b>J</b>) P-AKT, MMP2, and MMP13 was determined by Western blotting. Data are presented as the Mean ± SD (n = 3). <sup>ns</sup> <span class="html-italic">p</span> &gt; 0.05, * <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 compared with the control group.</p>
Full article ">Figure 7 Cont.
<p>SPV regulates p-AKT, MMP2, and MMP13 expression in U87 cells. (<b>A</b>–<b>F</b>) P-AKT, MMP2, and MMP13 was measured by immunofluorescence analysis of U87 cells treated with the series concentrations of SPV for 48 h. The cells were photographed (×200) and calculated by Image J (1.52i) software (n = 5). (<b>G</b>–<b>J</b>) P-AKT, MMP2, and MMP13 was determined by Western blotting. Data are presented as the Mean ± SD (n = 3). <sup>ns</sup> <span class="html-italic">p</span> &gt; 0.05, * <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 compared with the control group.</p>
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<p>SPV efficiently inhibits invasion, migration and adhesion in U87 cell through regulating <span class="html-italic">AKT</span> phosphorylation. (<b>A</b>,<b>B</b>) After SC79 and MK2206 intervention for 2 h, U87 cells treated with SPV for 48 h. Cell viability was determined by CCK8. (<b>C</b>,<b>F</b>) After SC79 and MK2206 intervention for 2 h, Transwell invasion assay of U87 cells treated for 36 h. (<b>D</b>,<b>G</b>) After SC79 and MK2206 intervention for 2 h, Transwell migration assay of U87 cells treated for 36 h. (<b>E</b>,<b>H</b>) Effect of SPV on the adhesion to Matrigel coated plate after 1 h exposure. The cells were photographed (×200) and calculated by Image J (1.52i) software (n = 5). Data are presented as the Mean ± SD (n = 5). <sup>ns</sup> <span class="html-italic">p</span> &gt; 0.05, ** <span class="html-italic">p</span> &lt; 0.01 and *** <span class="html-italic">p</span> &lt; 0.001 compared with the control 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 compared with SPV group.</p>
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<p>SPV affects the expression levels of MMP2 and MMP13 via regulating AKT phosphorylation in U87. (<b>A</b>–<b>F</b>) After SPV intervention for 48 h, immunofluorescence analysis was used to measure p-AKT, MMP2, and MMP13 of U87cells. The cells were photographed (×200) and calculated using Image J (1.52i) software (n = 5). Data are presented as the Mean ± SD (n = 5). <sup>ns</sup> <span class="html-italic">p</span> &gt; 0.05, ** <span class="html-italic">p</span> &lt; 0.01, and *** <span class="html-italic">p</span> &lt; 0.001 compared with the control 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 compared with SPV group.</p>
Full article ">Figure 9 Cont.
<p>SPV affects the expression levels of MMP2 and MMP13 via regulating AKT phosphorylation in U87. (<b>A</b>–<b>F</b>) After SPV intervention for 48 h, immunofluorescence analysis was used to measure p-AKT, MMP2, and MMP13 of U87cells. The cells were photographed (×200) and calculated using Image J (1.52i) software (n = 5). Data are presented as the Mean ± SD (n = 5). <sup>ns</sup> <span class="html-italic">p</span> &gt; 0.05, ** <span class="html-italic">p</span> &lt; 0.01, and *** <span class="html-italic">p</span> &lt; 0.001 compared with the control 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 compared with SPV group.</p>
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<p>SPV affects the expression levels of MMP2 and MMP13 in U87 via regulating AKT phosphorylation. (<b>A</b>–<b>D</b>) SC79 was added to cells 2 h before SPV intervention. After 48 h, Western blot was used to analyze p-AKT, MMP2, and MMP13 in U87. (<b>E</b>–<b>H</b>) MK2206 was added to cells 2 h before SPV intervention. After 48 h, p-AKT, MMP2, and MMP13 were analyzed via Western blotting. Data are presented as the Mean ± SD (n = 3). <sup>ns</sup> <span class="html-italic">p</span> &gt; 0.05, * <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 compared with the control group. ## <span class="html-italic">p</span> &lt; 0.01, and ### <span class="html-italic">p</span> &lt; 0.001 compared with SPV group.</p>
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16 pages, 2594 KiB  
Article
Myoblast-Derived Galectin 3 Impairs the Early Phases of Osteogenesis Affecting Notch and Akt Activity
by Emanuela Amore, Vittoria Cenni, Manuela Piazzi, Michele Signore, Giulia Orlandi, Simona Neri, Stefano Biressi, Rosario Barone, Valentina Di Felice, Matilde Y. Follo, Jessika Bertacchini and Carla Palumbo
Biomolecules 2024, 14(10), 1243; https://doi.org/10.3390/biom14101243 - 30 Sep 2024
Viewed by 498
Abstract
Galectin-3 (Gal-3) is a pleiotropic lectin produced by most cell types, which regulates multiple cellular processes in various tissues. In bone, depending on its cellular localization, Gal-3 has a dual and opposite role. If, on the one hand, intracellular Gal-3 promotes bone formation, [...] Read more.
Galectin-3 (Gal-3) is a pleiotropic lectin produced by most cell types, which regulates multiple cellular processes in various tissues. In bone, depending on its cellular localization, Gal-3 has a dual and opposite role. If, on the one hand, intracellular Gal-3 promotes bone formation, on the other, its circulating form affects bone remodeling, antagonizing osteoblast differentiation and increasing osteoclast activity. From an analysis of the secretome of cultured differentiating myoblasts, we interestingly found the presence of Gal-3. After that, we confirmed that Gal-3 was expressed and released in the extracellular environment from myoblast cells during their differentiation into myotubes, as well as after mechanical strain. An in vivo analysis revealed that Gal-3 was triggered by trained exercise and was specifically produced by fast muscle fibers. Speculating a role for this peptide in the muscle-to-bone cross talk, a direct co-culture in vitro system, simultaneously combining media that were obtained from differentiated myoblasts and osteoblast cells, confirmed that Gal-3 is a mediator of osteoblast differentiation. Molecular and proteomic analyses revealed that the secreted Gal-3 modulated the biochemical processes occurring in the early phases of bone formation, in particular impairing the activity of the STAT3 and PDK1/Akt signaling pathways and, at the same time, triggering that one of Notch. Circulating Gal-3 also affected the expression of the most common factors involved in osteogenetic processes, including BMP-2, -6, and -7. Intriguingly, Gal-3 was able to interfere with the ability of differentiating osteoblasts to interact with the components of the extracellular bone matrix, a crucial condition required for a proper osteoblast differentiation. All in all, our evidence lays the foundation for further studies to present this lectin as a novel myokine involved in muscle-to-bone crosstalk. Full article
(This article belongs to the Section Molecular Biology)
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Figure 1

Figure 1
<p>Muscle differentiation and mechanical stimulation trigger Gal-3 expression and release. (<b>A</b>) The C2C12 cells were differentiated for the indicated days. At the end of each time point, the cells and culture media were collected. The cells were lysed and, together with the culture media, were resolved by SDS-PAGE and explored for the Gal-3 level of expression. β-Tubulin and MyoD were used as loading and differentiation markers, respectively. Original images can be found in <a href="#app1-biomolecules-14-01243" class="html-app">Supplementary File 1</a>. (<b>B</b>) The densitometric values of intracellular and secreted Gal-3 were graphed in the bar histogram, shown aside. The densitometric results were normalized on the values of corresponding β-tubulin. * <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. (<b>C</b>,<b>D</b>) The differentiated C2C12 cells were subjected to multiaxial stretching (st) for 6 and 24 h, or left untreated (nt). At the end of the stimuli, the cells were lysed and, together with corresponding media, were subjected to an immunoblot analysis to verify the Gal-3 expression. The bars are relative to three different experiments, * <span class="html-italic">p</span> &lt; 0.05, ** <span class="html-italic">p</span> &lt; 0.01. (<b>E</b>) The cells, as in (<b>C</b>), were lysed in Trizol and subjected to an RT-PCR analysis for monitoring the level of expression of Gal-3 mRNA. The bars show the relative amount of Gal-3 mRNA. (<span class="html-italic">n</span> = 3 *** <span class="html-italic">p</span> ≤ 0.001). Original images can be found in <a href="#app1-biomolecules-14-01243" class="html-app">Supplementary File 1</a>.</p>
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<p>Endurance training increases Gal-3 expression in muscle fibers of type IIB. (<b>A</b>,<b>B</b>) The tibialis anterior muscles from the sedentary (Sed) and trained (Tr) mice groups were analyzed to determine the intracellular level of Gal-3 expression. The bar graph represents the average OD of the samples of the two groups, normalized to the corresponding values of GAPDH. Original images can be found in <a href="#app1-biomolecules-14-01243" class="html-app">Supplementary File 1</a>. (<b>C</b>,<b>D</b>) A Gal-3 immunohistochemical analysis of the red (RTA) and white fibers (WTA) of the tibialis anterior muscles from the sedentary and trained mice groups with the images’ signal intensity quantification. (<b>E</b>,<b>F</b>) The Gal-3 immunohistochemical analysis of the red (RGA) and white fibers (WGA) of the gastrocnemius muscles from the sedentary and trained mice groups, with the images’ signal intensity quantification. Enlarged areas are present within the most significant panels. Bars 250 micron. A statistically significant increase in Gal-3 expression was seen in the white fibers of both muscle types in the trained mice group (<span class="html-italic">n</span> = 3, * <span class="html-italic">p</span> &lt; 0.05), when compared to the group of sedentary mice.</p>
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<p>Gal-3 secreted by C2C12 cells impairs the osteogenic potential of the MC-3T3 osteoblast progenitor cells as a recombinant and as the soluble form of Gal-3. (<b>A</b>,<b>B</b>) The MC-3T3 cells were differentiated in the presence of a recombinant soluble form of Gal-3 (rec-Gal-3, FC 3 microg/mL) or another vehicle (vehicle) (<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) for three or seven days (D3 and D7, respectively). Where indicated, a combination of rec-Gal-3 and a specific antibody against Gal-3 was added (Gal-3 Ab, rabbit anti-Gal-3 1 µg/mL FC 3 µg/mL). As control, the MC-3T3 osteoblast progenitors were also collected at D0. The matrix bone mineralization was analyzed by alizarin red (AR) staining. After staining, the alizarin was diluted, quantified as described in the “Methods” Section, and the values were presented as a graph (<span class="html-italic">n</span> = 3, *** <span class="html-italic">p</span> &lt; 0.001). (<b>C</b>) The MC-3T3 osteoblast progenitors differentiated in the presence of rec-Gal-3 or another vehicle were harvested at D0, D3, and D7 and collected. One half of the cells’ pellet was then lysed and the total lysates were resolved and assayed for bone-alkaline phosphatase (ALP) and the Osterix level of expression. GAPDH was used as equal loading control. Original images can be found in <a href="#app1-biomolecules-14-01243" class="html-app">Supplementary File 1</a>. (<b>D</b>–<b>F</b>) The densitometric analysis of the level of expression of ALP and Osterix, normalized to GAPDH. (<b>E</b>) The other half of the cell pellets were lysed, and the ALP activity was monitored (<span class="html-italic">n</span> = 3, ** <span class="html-italic">p</span> ≤ 0.01). (<b>G</b>,<b>H</b>) The MC-3T3 osteoblast progenitors differentiated in the presence of rec-Gal-3 or another vehicle were harvested at D0, D3, and D7, lysed, and evaluated for Notch1 and cleaved Notch1 protein expression; a densitometric analysis was carried out, normalized on GAPDH levels, ** <span class="html-italic">p</span> ≤ 0.01. Original images can be found in <a href="#app1-biomolecules-14-01243" class="html-app">Supplementary File 1</a>. (<b>I</b>) The graph bar of the fold change of the level of expression of <span class="html-italic">Hey1</span> and <span class="html-italic">c-Myc</span> RNAs in D0- and D3-differentiated cells (with or without rec-Gal-3), relative to three different experiments (<span class="html-italic">n</span> = 3, * <span class="html-italic">p</span> &lt; 0.05, ** <span class="html-italic">p</span> ≤ 0.01). HPRT was used as a normalization housekeeping gene. (<b>J</b>,<b>K</b>) The MC-3T3 osteoblast precursor cells were maintained in the growth medium D0 and induced to differentiate in a canonical differentiation medium, D7, supplemented with the supernatant from the C2C12 cells that were overexpressing FLAG-Gal-3 (FLAG-Gal-3 OE, transfected for 48 h) or, as a control, from the C2C12 cells transfected with the empty vector (EV, transfected for 48 h). The differentiation medium (D7) was conditioned with the same amount of the C2C12 medium (EV and FLAG-Gal-3) in a medium ratio of 1:3. Samples were collected on the day of the change of the medium, D0, or at D7. The matrix bone mineralization was analyzed by alizarin red (AR) staining. The graph bars indicate the amount of AR staining (<span class="html-italic">n</span> = 3, *** <span class="html-italic">p</span> &lt; 0.001). (<b>L</b>) The MC-3T3 osteoblast progenitors were induced to differentiate in a canonical differentiation medium, D3, supplemented with the supernatant from the C2C12 cells that were subjected or not to a stretching protocol for 6 h. The differentiation medium (D3) was conditioned with one of the three C2C12 media (C2C12 media: not stretched, stretched for 6 h, or stretched for 6 h + neutralizing antibody). The total lysates were resolved and assayed for the bone-alkaline phosphatase (ALP) level of activity (<span class="html-italic">n</span> = 3, * <span class="html-italic">p</span> &lt; 0.05, ** <span class="html-italic">p</span> ≤ 0.01). (<b>M</b>) An RT-qPCR analysis of RUNX2 expression in the MC-3T3 cells differentiated as in M) (<span class="html-italic">n</span> = 3, ** <span class="html-italic">p</span> ≤ 0.01).</p>
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<p>Rec-Gal-3 modulates the expression of proteins with fundamental cellular functions during the differentiation of MC-3T3 osteoprogenitor cells. (<b>A</b>) A Venn diagram showing the proteins identified by an LC-MS analysis. We identified 117 proteins on D0, 366 on D3, and 353 on D3 + rec-Gal-3. (<b>B</b>) The list of proteins up- or down-regulated in the MC-3T3 cells after 3 days of differentiation with recombinant Gal-3, compared to D3. Only the proteins identified with a fold increase ≥ 4 were reported.</p>
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<p>Mechanistic insights into circulating Gal-3 functions during the differentiation of MC-3T3 osteoprogenitor cells. (<b>A</b>) Heat map showing the phosphorylation of the main signaling pathways detected by the RPPA analysis during the growing state (D0), the early (D3), and the middle (D7) phases of the differentiation of the MC-3T3 cells with or without rec-Gal-3. Squared phosphorylated proteins are the species most impaired by Gal-3 supplementation. The values are reported as the mean of signal intensities, with <span class="html-italic">n</span> = 3. (<b>B</b>) The level of expression of the proteins promoting osteogenesis during the differentiation of the MC-3T3 cells with or without rec-Gal-3 (+rec-Gal-3) through the “Bone Metabolism Antibody Array”. The cells were blocked on D0 and D3 (<span class="html-italic">n</span> = 3, * <span class="html-italic">p</span> ≤ 0.05; ** <span class="html-italic">p</span> ≤ 0.01).</p>
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<p>rec-Gal-3 affects the ability of differentiated osteoblasts to interact with ECM components. The evaluation of the ability of the MC-3T3 cells maintained in a growth medium (D0), differentiated for 3 days (D3) with or without recombinant Gal-3 (D3 + rec-Gal-3) to interact with the typical components of the extracellular bone matrix (Collagen I, Fibronectin, Laminin) through the “ECM adhesion assay” (<span class="html-italic">n</span> = 2, * <span class="html-italic">p</span> ≤ 0.05; ** <span class="html-italic">p</span> ≤ 0.01).</p>
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14 pages, 2036 KiB  
Article
EDA Variants Are Responsible for Approximately 90% of Deciduous Tooth Agenesis
by Lanxin Su, Bichen Lin, Miao Yu, Yang Liu, Shichen Sun, Hailan Feng, Haochen Liu and Dong Han
Int. J. Mol. Sci. 2024, 25(19), 10451; https://doi.org/10.3390/ijms251910451 - 27 Sep 2024
Viewed by 314
Abstract
Deciduous tooth agenesis is a severe craniofacial developmental defect because it affects masticatory function from infancy and may result in delayed growth and development. Here, we aimed to identify the crucial pathogenic genes and clinical features of patients with deciduous tooth agenesis. We [...] Read more.
Deciduous tooth agenesis is a severe craniofacial developmental defect because it affects masticatory function from infancy and may result in delayed growth and development. Here, we aimed to identify the crucial pathogenic genes and clinical features of patients with deciduous tooth agenesis. We recruited 84 patients with severe deciduous tooth agenesis. Whole-exome and Sanger sequencing were used to identify the causative variants. Phenotype–genotype correlation analysis was conducted. We identified 54 different variants in 8 genes in 84 patients, including EDA (73, 86.9%), PAX9 (2, 2.4%), LRP6 (2, 2.4%), MSX1 (2, 2.4%), BMP4 (1, 1.2%), WNT10A (1, 1.2%), PITX2 (1, 1.2%), and EDARADD (1, 1.2%). Variants in ectodysplasin A (EDA) accounted for 86.9% of patients with deciduous tooth agenesis. Patients with the EDA variants had an average of 15.4 missing deciduous teeth. Mandibular deciduous central incisors had the highest missing rate (100%), followed by maxillary deciduous lateral incisors (98.8%) and mandibular deciduous lateral incisors (97.7%). Our results indicated that EDA gene variants are major pathogenic factors for deciduous tooth agenesis, and EDA is specifically required for deciduous tooth development. The results provide guidance for clinical diagnosis and genetic counseling of deciduous tooth agenesis. Full article
(This article belongs to the Section Molecular Genetics and Genomics)
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Figure 1

Figure 1
<p>Variants found in the patient cohort. (<b>A</b>,<b>B</b>) Number and percentage of patients with different variants identified in this study. (<b>C</b>) Proportion of different <span class="html-italic">EDA</span> variants.</p>
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<p>Localization of the 43 <span class="html-italic">EDA</span> variants. (<b>A</b>) Number and distribution of <span class="html-italic">EDA</span> variants in different exons and domains. (<b>B</b>) Schematic diagram of the wild-type ectodysplasin A protein and the localization of the <span class="html-italic">EDA</span> variants identified in this study. TM, transmembrane; TNF, tumor necrosis factor.</p>
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<p>Dental phenotype of the 43 patients with <span class="html-italic">EDA</span> variants. (<b>A</b>) Count and percentage of missing deciduous teeth at each position in maxillary and mandibular dentition. (<b>B</b>,<b>C</b>) Proportion of absence at five positions in maxillary and mandibular dentition, respectively. Asterisks indicate significant differences (* <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). (<b>D</b>) Schema showing the missing frequencies at each deciduous tooth position. A darker color indicates higher rates. Max, maxillary; Mand, mandibular; R, right; L, left; dCI, deciduous central incisor; dLI, deciduous lateral incisor; dC, deciduous canine; dM1, first deciduous molar; dM2, second deciduous molar.</p>
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<p>Distribution of missing deciduous teeth due to different <span class="html-italic">EDA</span> variant types and locations. (<b>A</b>) Mean number of missing deciduous teeth in patients with different <span class="html-italic">EDA</span> variant types. (<b>B</b>) Mean number of missing deciduous teeth in patients with <span class="html-italic">EDA</span> variants situated at the four domains. (<b>C</b>) Rates of maxillary and mandibular missing deciduous teeth at five positions caused by variants in different domains. Asterisks indicate significant differences (* <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). TM, transmembrane domain; TNF, tumor necrosis factor homologous domain; dCI, deciduous central incisor; dLI, deciduous lateral incisor; dC, deciduous canine; dM1, first deciduous molar; dM2, second deciduous molar.</p>
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14 pages, 2561 KiB  
Article
BMP4 and Temozolomide Synergize in the Majority of Patient-Derived Glioblastoma Cultures
by Iris S. C. Verploegh, Andrea Conidi, Hoesna El Hassnaoui, Floor A. M. Verhoeven, Anne L. Korporaal, Ioannis Ntafoulis, Mirjam C. G. N. van den Hout, Rutger W. W. Brouwer, Martine L. M. Lamfers, Wilfred F. J. van IJcken, Danny Huylebroeck and Sieger Leenstra
Int. J. Mol. Sci. 2024, 25(18), 10176; https://doi.org/10.3390/ijms251810176 - 22 Sep 2024
Viewed by 635
Abstract
One of the main causes of poor prognoses in patient with glioblastoma (GBM) is drug resistance to current standard treatment, which includes chemoradiation and adjuvant temozolomide (TMZ). In addition, the concept of cancer stem cells provides new insights into therapy resistance and management [...] Read more.
One of the main causes of poor prognoses in patient with glioblastoma (GBM) is drug resistance to current standard treatment, which includes chemoradiation and adjuvant temozolomide (TMZ). In addition, the concept of cancer stem cells provides new insights into therapy resistance and management also in GBM and glioblastoma stem cell-like cells (GSCs), which might contribute to therapy resistance. Bone morphogenetic protein-4 (BMP4) stimulates astroglial differentiation of GSCs and thereby reduces their self-renewal capacity. Exposure of GSCs to BMP4 may also sensitize these cells to TMZ. A recent phase I trial has shown that local delivery of BMP4 is safe, but a large variation in survival is seen in these treated patients and in features of their cultured tumors. We wanted to combine TMZ and BMP4 (TMZ + BMP4) therapy and assess the inter-tumoral variability in response to TMZ + BMP4 in patient-derived GBM cultures. A phase II trial could then benefit a larger group of patients than those treated with BMP4 only. We first show that simultaneous treatment with TMZ + BMP4 is more effective than sequential treatment. Second, when applying our optimized treatment protocol, 70% of a total of 20 GBM cultures displayed TMZ + BMP4 synergy. This combination induces cellular apoptosis and does not inhibit cell proliferation. Comparative bulk RNA-sequencing indicates that treatment with TMZ + BMP4 eventually results in decreased MAPK signaling, in line with previous evidence that increased MAPK signaling is associated with resistance to TMZ. Based on these results, we advocate further clinical trial research to test patient benefit and validate pathophysiological hypothesis. Full article
(This article belongs to the Special Issue Biomechanics and Molecular Research on Glioblastoma)
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<p>Combination therapy TMZ + BMP4 is generally more effective than sequential therapy: (<b>a</b>) schematic representation of the treatment protocol per day, starting on day-1 (D-1); (<b>b</b>) mean cell viability with standard deviation (n = 3) on day 7 of treatment normalized to untreated cells. ** <span class="html-italic">p</span> &lt; 0.01, *** <span class="html-italic">p</span> &lt; 0.001.</p>
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<p>GBM cell culture viability after treatment with temozolomide (TMZ) and BMP4. Average cell viability (n = 3) in cultures GS755 (<b>a</b>), GS838 (<b>b</b>), and GS786 (<b>c</b>) after 7 days of treatment with a 3-fold dilution ranging from 180 ng down to 0.74 ng BMP4/mL (blue) and 360 µM down to 1.5 µM TMZ (red) and a combination of both (yellow). The lowest dose is depicted in white (1.5 µM TMZ; 0.75 ng BMP4/mL) increasing (4.5 µM/2.25 ng/mL; 13.5 µM/6.8 ng/mL; 40 µM/20 ng/mL; 120 µM/60 ng/mL) to the highest dose depicted in dark grey (360 µM TMZ and 180 ng BMP4/mL). (<b>d</b>) Heat map of HSA score per dose and culture. A low HSA score (antagonism) is depicted in blue and a high score (synergy) is shown in red. The bars above the figure represent the sensitivity (black) or resistance (white) to TMZ (EC50 &gt; 100 µM) and BMP4 (EC50 &gt; 60 ng/mL).</p>
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<p>Effects of temozolomide (TMZ) and BMP4 on GBM culture cell proliferation and apoptosis. Average percentage of proliferating cells (EdU+) (<b>a</b>) and apoptotic cells (annexin-V+) (<b>b</b>) with standard deviation (n = 3) in untreated condition (gray) and after treatment with TMZ (red), BMP4 (blue), and TMZ + BMP4 (yellow). * <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, ns = not significant. No further specified comparisons were considered statistically significant.</p>
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<p>Venn diagram of DEGs (<span class="html-italic">p</span> &lt; 0.01, log FC &gt; 1.5) treated compared with untreated cells per culture, where upregulated genes are red and downregulated cells are blue.</p>
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<p>Exclusive differentially expressed genes (DEGs) after monotherapy with BMP4. (<b>a</b>) Heatmap of the top 10 most up- (red) and downregulated (blue) genes after treatment with TMZ, BMP4, and TMZ + BMP4, which are unique for monotherapy with BMP4, per sequenced culture. (<b>b</b>) Overlap of genes that were uniquely differentially expressed after monotherapy with BMP4 per culture. Purple lines linking identical genes. (<b>c</b>) Heat map of gene set enrichment analysis of DEGs unique after BMP4 monotherapy.</p>
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<p>Exclusive differentially expressed genes (DEGs) after combination therapy with TMZ and BMP4. (<b>a</b>) Heat map of the top 10 most upregulated (red) and downregulated (blue) genes after treatment with TMZ, BMP4, and TMZ + BMP4, which are unique for combination therapy of TMZ + BMP4, per sequenced culture. (<b>b</b>) Overlap of genes that were uniquely differentially expressed after monotherapy with BMP4 per culture. Purple lines link identical genes and blue lines link genes that belong to similar enriched ontology terms. Genes marked in red are common between GS627 and GS838, green between GS627 and GS755, and black between GS755 and GS838. (<b>c</b>) Heatmap of gene set enrichment analysis of unique DEGs after treatment with BMP4 and TMZ.</p>
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22 pages, 4084 KiB  
Review
Airport Runoff Water: State-of-the-Art and Future Perspectives
by Anna Maria Sulej-Suchomska, Danuta Szumińska, Miguel de la Guardia, Piotr Przybyłowski and Żaneta Polkowska
Sustainability 2024, 16(18), 8176; https://doi.org/10.3390/su16188176 - 19 Sep 2024
Viewed by 793
Abstract
The increase in the quantity and variety of contaminants generated during routine airport infrastructure maintenance operations leads to a wider range of pollutants entering soil and surface waters through runoff, causing soil erosion and groundwater pollution. A significant developmental challenge is ensuring that [...] Read more.
The increase in the quantity and variety of contaminants generated during routine airport infrastructure maintenance operations leads to a wider range of pollutants entering soil and surface waters through runoff, causing soil erosion and groundwater pollution. A significant developmental challenge is ensuring that airport infrastructure meets high-quality environmental management standards. It is crucial to have effective tools for monitoring and managing the volume and quality of stormwater produced within airports and nearby coastal areas. It is necessary to develop methodologies for determining a wide range of contaminants in airport stormwater samples and assessing their toxicity to improve the accuracy of environmental status assessments. This manuscript aims to showcase the latest advancements (2010–2024 update) in developing methodologies, including green analytical techniques, for detecting a wide range of pollutants in airport runoff waters and directly assessing the toxicity levels of airport stormwater effluent. An integrated chemical and ecotoxicological approach to assessing environmental pollution in airport areas can lead to precise environmental risk assessments and well-informed management decisions for sustainable airport operations. Furthermore, this critical review highlights the latest innovations in remediation techniques and various strategies to minimize airport waste. It shifts the paradigm of soil and water pollution management towards nature-based solutions, aligning with the sustainable development goals of the 2030 Agenda. Full article
(This article belongs to the Special Issue Geological Environment Monitoring and Early Warning Systems)
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<p>The most important sources of pollution at airports.</p>
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<p>Percentage distribution of the most commonly analyzed inorganic (<b>a</b>) and organic (<b>b</b>) analytes in runoff water samples from airports across various countries.</p>
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<p>Percentage distribution of the conducted toxicity tests on airport runoff water samples in various countries.</p>
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<p>Pie chart of scientific publications on xenobiotic determination in airport runoff water samples, categorized by country and number of publications.</p>
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<p>Hypothetical airport layout illustrating the main operational areas of airport infrastructure, numbered (1)–(8) according to the descriptions in <a href="#sustainability-16-08176-t001" class="html-table">Table 1</a>.</p>
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16 pages, 13656 KiB  
Article
Regeneration of Critical Calvarial Bone Defects Using Bovine Xenograft, Magnesium-Enriched Bovine Xenograft and Autologous Dentin in Rats: Micro-CT, Gene Expression and Immunohistochemical Analysis
by Marija Čandrlić, Ana Terezija Jerbić Radetić, Hrvoje Omrčen, Barbara Franović, Lara Batičić, Tamara Gulić, Tea Čaljkušić-Mance, Sanja Zoričić Cvek, Lucija Malešić, Željka Perić Kačarević and Olga Cvijanović Peloza
J. Funct. Biomater. 2024, 15(9), 270; https://doi.org/10.3390/jfb15090270 - 18 Sep 2024
Viewed by 956
Abstract
The aim of this study was to evaluate the efficacy of autologous dentin (AD), bovine xenograft (BX) and magnesium-enriched bovine xenograft (BX + Mg) in the healing of critical cranial bone defects (CCBDs) in rats. Eighty male Wistar rats were divided into four [...] Read more.
The aim of this study was to evaluate the efficacy of autologous dentin (AD), bovine xenograft (BX) and magnesium-enriched bovine xenograft (BX + Mg) in the healing of critical cranial bone defects (CCBDs) in rats. Eighty male Wistar rats were divided into four groups: BX, BX + Mg, AD and the control group (no intervention). Eight mm CCBDs were created and treated with the respective biomaterials. Healing was assessed 7, 15, 21 and 30 days after surgery by micro-computed tomography (micro-CT), real-time polymerase chain reaction (RT-PCR) and immunohistochemical analysis. Micro-CT analysis showed that AD had the highest bone volume and the least amount of residual biomaterial at day 30, indicating robust bone formation and efficient resorption. BX + Mg showed significant bone volume but had more residual biomaterial compared to AD. RT-PCR showed that the expression of osteocalcin (OC), the receptor activator of nuclear factor κB (RANK) and sclerostin (SOST), was highest in the AD group at day 21 and vascular endothelial growth factor (VEGF) at day 15, indicating increased osteogenesis and angiogenesis in the AD group. Immunohistochemical staining confirmed intense BMP-2/4 and SMAD-1/5/8 expression in the AD group, indicating osteoinductive properties. The favorable gene expression profile and biocompatibility of AD and BX + Mg make them promising candidates for clinical applications in bone tissue engineering. Further research is required to fully exploit their potential in regenerative surgery. Full article
(This article belongs to the Special Issue Functional Biomaterial for Bone Regeneration)
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<p>Visualization of the fronto-parieto-occipital complex of the calvaria of rats, imaged with a micro-CT device. The images show the progression of CCBD closure over the days of healing.</p>
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<p>The expressions of RANK, SOST and OC were highest in the AD group on day 21 of healing. The VEGF expression was also highest in the AD group, but on the 15th day of healing.</p>
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<p>BMP-2/4 immunohistochemical staining of coronal sections of calvarial bone defects in the following groups: BX—bovine xenograft (<b>A</b>–<b>D</b>); BX + MG—bovine xenograft and magnesium (<b>E</b>–<b>H</b>); AD—autologous dentin (<b>I</b>–<b>L</b>); and control group (<b>M</b>–<b>P</b>) on the 7th, 15th, 21st and 30th day. Legend of abbreviations. The BMP-2/4 immunohistochemical staining of the coronal sections of the calvarial bone defects are shown for the following groups: BX—bovine xenograft (<b>A</b>–<b>D</b>); BX + MG—bovine xenograft; BM—biomaterial; NB—new bone formation; BV—blood vessel. Triangles (▲) indicate osteoblasts and osteocytes in lacunae, asterisks (★) indicate immunopositive multinucleated cells, and arrows (↑) indicate sites of bone bridging and apposition. On the right side of the immunohistochemistry slides, there are diagrams showing the immunohistochemical staining for each biomaterial broken down by day, on days 7, 15, 21 and 30 of healing.</p>
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<p>SMAD-1/5/8 immunohistochemical staining of coronal sections of calvarial bone defects for the following groups: BX—bovine xenograft (<b>A</b>–<b>D</b>); BX + MG—bovine xenograft and magnesium (<b>E</b>–<b>H</b>); AD—autologous dentin (<b>I</b>–<b>L</b>); and control group (<b>M</b>–<b>P</b>) on the 7th, 15th, 21st and 30th day. Legend of abbreviations: BM—biomaterial; NB—new bone formation; BV—blood vessel. Triangles (▲) indicate osteoblasts and osteocytes in lacunae, asterisks (★) indicate immunopositive multinucleated cells, and arrows (↑) indicate sites of bone bridging and apposition. On the right side of the immunohistochemistry slides, there are diagrams showing the immunohistochemical staining for each biomaterial broken down by day, on days 7, 15, 21 and 30 of healing.</p>
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<p>VEGF immunohistochemical staining of coronal sections of calvarial bone defects for the following groups: BX—bovine xenograft (<b>A</b>–<b>D</b>); BX + MG—bovine xenograft and magnesium (<b>E</b>–<b>H</b>); AD—autologous dentin (<b>I</b>–<b>L</b>); and control group (<b>M</b>–<b>P</b>) on the 7th, 15th, 21st and 30th day. Legend of abbreviations: BM—biomaterial; NB—new bone formation; BV—blood vessel. Triangles (▲) indicate osteoblasts and osteocytes in lacunae, asterisks (★) indicate immunopositive multinucle-ated cells, and arrows (↑) indicate sites of bone bridging and apposition. On the right side of the immunohistochemistry slides; there are diagrams showing the immunohistochemical staining for each biomaterial broken down by day, on days 7, 15, 21 and 30 of healing.</p>
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34 pages, 795 KiB  
Review
Onco-Ontogeny of Squamous Cell Cancer of the First Pharyngeal Arch Derivatives
by Daniel Sat-Muñoz, Luz-Ma.-Adriana Balderas-Peña, Eduardo Gómez-Sánchez, Brenda-Eugenia Martínez-Herrera, Benjamín Trujillo-Hernández, Luis-Aarón Quiroga-Morales, Mario Salazar-Páramo, Ingrid-Patricia Dávalos-Rodríguez, Carlos M. Nuño-Guzmán, Martha-Cecilia Velázquez-Flores, Miguel-Ricardo Ochoa-Plascencia, María-Ivette Muciño-Hernández, Mario-Alberto Isiordia-Espinoza, Mario-Alberto Mireles-Ramírez and Eduardo Hernández-Salazar
Int. J. Mol. Sci. 2024, 25(18), 9979; https://doi.org/10.3390/ijms25189979 - 16 Sep 2024
Viewed by 920
Abstract
Head and neck squamous cell carcinoma (H&NSCC) is an anatomic, biological, and genetic complex disease. It involves more than 1000 genes implied in its oncogenesis; for this review, we limit our search and description to the genes implied in the onco-ontogeny of the [...] Read more.
Head and neck squamous cell carcinoma (H&NSCC) is an anatomic, biological, and genetic complex disease. It involves more than 1000 genes implied in its oncogenesis; for this review, we limit our search and description to the genes implied in the onco-ontogeny of the derivates from the first pharyngeal arch during embryo development. They can be grouped as transcription factors and signaling molecules (that act as growth factors that bind to receptors). Finally, we propose the term embryo-oncogenesis to refer to the activation, reactivation, and use of the genes involved in the embryo’s development during the oncogenesis or malignant tumor invasion and metastasis events as part of an onco-ontogenic inverse process. Full article
(This article belongs to the Special Issue Pathogenesis and Therapy of Oral Carcinogenesis, 2nd Edition)
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<p>Factors related to malignant transformation in structures derivatives of the pharyngeal arches and pouches (to the genes and factors actions see description in <a href="#ijms-25-09979-t002" class="html-table">Table 2</a>).</p>
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13 pages, 3580 KiB  
Article
Novel Function of Osteocalcin in Chondrocyte Differentiation and Endochondral Ossification Revealed on a CRISPR/Cas9 bglap–bglap2 Deficiency Mouse Model
by Xiang-Fang Yu, Bin Teng, Jun-Feng Li, Jian V. Zhang, Zhe Su and Pei-Gen Ren
Int. J. Mol. Sci. 2024, 25(18), 9945; https://doi.org/10.3390/ijms25189945 - 15 Sep 2024
Viewed by 620
Abstract
Endochondral ossification is the process by which cartilage is mineralized into bone, and is essential for the development of long bones. Osteocalcin (OCN), a protein abundant in bone matrix, also exhibits high expression in chondrocytes, especially hypertrophic chondrocytes, while its role in endochondral [...] Read more.
Endochondral ossification is the process by which cartilage is mineralized into bone, and is essential for the development of long bones. Osteocalcin (OCN), a protein abundant in bone matrix, also exhibits high expression in chondrocytes, especially hypertrophic chondrocytes, while its role in endochondral ossification remains unclear. Utilizing a new CRISPR/Cas9-mediated bglap–bglap2 deficiency (OCNem) mouse model generated in our laboratory, we provide the first evidence of OCN’s regulatory function in chondrocyte differentiation and endochondral ossification. The OCNem mice exhibited significant delays in primary and secondary ossification centers compared to wild-type mice, along with increased cartilage length in growth plates and hypertrophic zones during neonatal and adolescent stages. These anomalies indicated that OCN deficiency disturbed endochondral ossification during embryonic and postnatal periods. Mechanism wise, OCN deficiency was found to increase chondrocyte differentiation and postpone vascularization process. Furthermore, bone marrow mesenchymal stromal cells (BMSCs) from OCNem mice demonstrated an increased capacity for chondrogenic differentiation. Transcriptional network analysis implicated that BMP and TGF-β signaling pathways were highly affected in OCNem BMSCs, which is closely associated with cartilage development and maintenance. This elucidation of OCN’s function in chondrocyte differentiation and endochondral ossification contributes to a more comprehensive understanding of its impact on skeletal development and homeostasis. Full article
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<p>CRISPR/Cas9-mediated <span class="html-italic">bglap–bglap2</span> deficiency (OCN<sup>em</sup>) mice delayed development of early endochondral ossification and shortened primary ossification center (POC) in embryonic period. (<b>A</b>) Gross morphology of WT and OCN<sup>em</sup> mice. (<b>B</b>) Body length. (<b>C</b>–<b>E</b>) Alizarin red S/alcian blue staining on hindlimbs of WT and OCN<sup>em</sup> mice; L: left, R: right. (<b>C</b>) Metacarpals ossification at E17.5; arrows indicated metacarpal POC, scale bars: 500 μm. (<b>D</b>) Metacarpals/phalanges ossification at P0; ovals circled the middle phalangeal POC, scale bars: 500 μm. (<b>E</b>) Femurs and tibias ossification at E15.5, E17.5, and P0; dot lines indicated femoral and tibial POC, scale bars: 2 mm. (<b>F</b>,<b>G</b>) Quantification of the POC length of femur and tibia. There were 5 mice in each group, no samples were excluded and all data were expressed as mean ± SD. The statistical significance was denoted as * <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 by Student’s <span class="html-italic">t</span>-test.</p>
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<p>The formation of secondary ossification centers (SOCs) was delayed in OCN<sup>em</sup> mice after birth. (<b>A</b>) Representative safranin O/fast green staining of the proximal tibia of WT and OCN<sup>em</sup> mice at P7, P14 and P21 (Scale bars: 100 μm). AC: articular cartilage; gray dashed line outlined the SOC. Quantification of the SOC size (<b>B</b>) and AC thickness (<b>C</b>). There were 5 mice in each group, no samples were excluded and all data were expressed as mean ± SD. The statistical significance was denoted as ** <span class="html-italic">p</span> &lt; 0.01, *** <span class="html-italic">p</span> &lt; 0.001 by Student’s <span class="html-italic">t</span>-test.</p>
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<p>Knockout of OCN significantly increased the cartilage length. (<b>A</b>,<b>B</b>) Representative safranin O/fast green staining of tibial growth plate (GP) (upper panel) and higher magnification view of hypertrophic zone (HZ) (lower panel) of WT and OCN<sup>em</sup> mice at P0 (<b>A</b>) and P21 (<b>B</b>). At upper panel, black dashed lines indicated growth plates (Scale bars: 100 μm); at lower panel, gray dashed lines outlined HZ (Scale bars: 50 μm). (<b>C</b>,<b>D</b>) Quantification of the overall length of GP, PZ and HZ at P0 (<b>C</b>) and P21 (<b>D</b>). GP: growth plate, PZ: proliferative zone, HZ: hypertrophic zone. There were 5 mice in each group, no samples were excluded and all data were expressed as mean ± SD. The statistical significance was denoted as * <span class="html-italic">p</span> &lt; 0.05 by Student’s <span class="html-italic">t</span>-test.</p>
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<p>Knockout of OCN increased chondrocyte differentiation and postponed vascularization process. (<b>A</b>) IF staining to detect proliferation, differentiation and vascular invasion markers in mice growth plate. Scale bars: 200 μm; (<b>B</b>–<b>E</b>) Quantification of the expression of PCNA, Col II, MMP 13, and VEGF in the growth plate. There were 5 mice in each group, no samples were excluded and all data were expressed as mean ± SD. The statistical significance was denoted as * <span class="html-italic">p</span> &lt; 0.05, ** <span class="html-italic">p</span> &lt; 0.01 by Student’s <span class="html-italic">t</span>-test.</p>
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<p>Knockout of OCN decreased the differentiation potential of bone marrow mesenchymal stromal cells (BMSCs) to bone, but more importantly increased the differentiation potential to cartilage. (<b>A</b>) A volcano plot illustrating differentially regulated gene expression between the WT and OCN<sup>em</sup> BMSCs. Values are presented as the log10 of tag counts; (<b>B</b>) The GO functional clustering of differentially expressed genes associated with chondrogenesis and osteogenesis process. * means this biological process was affected; (<b>C</b>,<b>D</b>) GSEA analyzed the genes associated with osteoblast development and chondrocyte development. NES, normalized enrichment score; FDR, false discovery rate. There were 3 samples in each group and no samples were excluded.</p>
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<p>Chondrogenic differentiation of BMSCs from OCN<sup>em</sup> mice was significantly enhanced. (<b>A</b>) Photomicrographs of WT BMSCs and OCN<sup>em</sup> BMSCs pellets on days 14 and 28 stained with alcian blue/nuclear fast red staining. Scale bars: 50 μm; (<b>B</b>) Quantified the percentage of alcian blue positive area; (<b>C</b>) sGAG content in WT BMSCs and OCN<sup>em</sup> BMSC pellets on day 14 and 28; (<b>D</b>,<b>E</b>) Detection of chondrogenic differentiation–related genes <span class="html-italic">Col2a1</span> expression by RT–qPCR and RNA–sequencing; (<b>F</b>) GSEA analyzed the genes associated with cartilage development; (<b>G</b>) Transcriptional network of the differentially expressed genes related to cartilage development, BMP signaling and TGF–β signaling. The node size was set based on foldchange in the differentially expressed genes. Red-colored circles indicate genes present in 2 or more purple–colored circles. There were more than 3 samples in each group, no samples were excluded and all data were expressed as mean ± SD. The statistical significance was denoted as ** <span class="html-italic">p</span> &lt; 0.01, *** <span class="html-italic">p</span> &lt; 0.001 by Student’s <span class="html-italic">t</span>-test.</p>
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