Nothing Special   »   [go: up one dir, main page]

You seem to have javascript disabled. Please note that many of the page functionalities won't work as expected without javascript enabled.
 
 
Sign in to use this feature.

Years

Between: -

Subjects

remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline

Journals

remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline

Article Types

Countries / Regions

remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline

Search Results (12,098)

Search Parameters:
Keywords = line-by-line processing

Order results
Result details
Results per page
Select all
Export citation of selected articles as:
14 pages, 3964 KiB  
Article
Influence of Polymer Film Thickness on Drug Release from Fluidized Bed Coated Pellets and Intended Process and Product Control
by Marcel Langner, Florian Priese and Bertram Wolf
Pharmaceutics 2024, 16(10), 1307; https://doi.org/10.3390/pharmaceutics16101307 (registering DOI) - 8 Oct 2024
Abstract
Background/Objectives: Coated drug pellets enjoy widespread use in hard gelatine capsules. In heterogeneous pellets, the drug substance is layered onto core pellets. Coatings are often applied to generate a retarded release or an enteric coating. Methods: In the present study, the thickness of [...] Read more.
Background/Objectives: Coated drug pellets enjoy widespread use in hard gelatine capsules. In heterogeneous pellets, the drug substance is layered onto core pellets. Coatings are often applied to generate a retarded release or an enteric coating. Methods: In the present study, the thickness of a polymer coating layer on drug pellets was correlated to the drug release kinetics. Results: The question should be answered whether it is possible to stop the coating process when a layer thickness referring to an intended drug release is achieved. Inert pellets were first coated with sodium benzoate and second with different amounts of water insoluble polyacrylate in a fluidized bed apparatus equipped with a Wurster inlet. The whole process was controlled in-line and at-line with process analytical technology by the measurement of the particle size and the layer thickness. The in-vitro sodium benzoate release was investigated, and the data were linearized by different standard models and compared with the polyacrylate layer thickness. With increasing polyacrylate layer thickness the release rate diminishes. The superposition of several processes influencing the release results in release profiles corresponding approximately to first order kinetics. The coating layer thickness corresponds to a determined drug release profile. Conclusions: The manufacturing of coated drug pellets with intended drug release is possible by coating process control and layer thickness measurement. Preliminary investigations are necessary for different formulations. Full article
(This article belongs to the Special Issue Impact of Raw Material Properties on Solid Dosage Form Processes)
Show Figures

Figure 1

Figure 1
<p>SEM photograph of a polyacrylate coated SB pellet.</p>
Full article ">Figure 2
<p>Double linear plot of the sodium benzoate release, SB pellets without polyacrylate layer, experimental release from polyacrylate-coated lots P1, P2 and P3 with increasing layer thickness and calculated release P1cal, P2cal and P3cal.</p>
Full article ">Figure 3
<p>First order Sigma minus function of the experimental and calculated (cal) sodium benzoate release, lots P1, P2 and P3.</p>
Full article ">Figure 4
<p>First order Weibull function of the experimental sodium benzoate release, lots P1, P2 and P3.</p>
Full article ">Figure 5
<p>Weibull function release parameter t<sub>63.2%</sub> versus coating layer thickness, lots P1 (coefficient of determination 0.87, polyacrylate content 6.5%), P2 (0.99, 10.5%) and P3 (0.99, 16.1%).</p>
Full article ">Figure 6
<p>Square root function of the experimental sodium benzoate release, lots P1, P2 and P3.</p>
Full article ">Figure 7
<p>Cubic root function of the experimental sodium benzoate release, lots P1, P2 and P3.</p>
Full article ">
37 pages, 14053 KiB  
Review
Advances in Cancer Therapy: A Comprehensive Review of CDK and EGFR Inhibitors
by Mohammed Hawash
Cells 2024, 13(19), 1656; https://doi.org/10.3390/cells13191656 - 6 Oct 2024
Viewed by 414
Abstract
Protein kinases have essential responsibilities in controlling several cellular processes, and their abnormal regulation is strongly related to the development of cancer. The implementation of protein kinase inhibitors has significantly transformed cancer therapy by modifying treatment strategies. These inhibitors have received substantial FDA [...] Read more.
Protein kinases have essential responsibilities in controlling several cellular processes, and their abnormal regulation is strongly related to the development of cancer. The implementation of protein kinase inhibitors has significantly transformed cancer therapy by modifying treatment strategies. These inhibitors have received substantial FDA clearance in recent decades. Protein kinases have emerged as primary objectives for therapeutic interventions, particularly in the context of cancer treatment. At present, 69 therapeutics have been approved by the FDA that target approximately 24 protein kinases, which are specifically prescribed for the treatment of neoplastic illnesses. These novel agents specifically inhibit certain protein kinases, such as receptor protein-tyrosine kinases, protein-serine/threonine kinases, dual-specificity kinases, nonreceptor protein-tyrosine kinases, and receptor protein-tyrosine kinases. This review presents a comprehensive overview of novel targets of kinase inhibitors, with a specific focus on cyclin-dependent kinases (CDKs) and epidermal growth factor receptor (EGFR). The majority of the reviewed studies commenced with an assessment of cancer cell lines and concluded with a comprehensive biological evaluation of individual kinase targets. The reviewed articles provide detailed information on the structural features of potent anticancer agents and their specific activity, which refers to their ability to selectively inhibit cancer-promoting kinases including CDKs and EGFR. Additionally, the latest FDA-approved anticancer agents targeting these enzymes were highlighted accordingly. Full article
Show Figures

Figure 1

Figure 1
<p>(<b>a</b>) The crystal structure of CDK2/CyclinA with Flavopiridol (PDB: 6GUB). (<b>b</b>) The binding interactions between Flavopiridol and certain residues in side CDK2. (<b>c</b>) The crystal structure of CDK4/CyclinD with abemaciclib (PDB: 7SJ3). (<b>d</b>) The binding interactions between abemaciclib and certain residues in side CDK4.</p>
Full article ">Figure 1 Cont.
<p>(<b>a</b>) The crystal structure of CDK2/CyclinA with Flavopiridol (PDB: 6GUB). (<b>b</b>) The binding interactions between Flavopiridol and certain residues in side CDK2. (<b>c</b>) The crystal structure of CDK4/CyclinD with abemaciclib (PDB: 7SJ3). (<b>d</b>) The binding interactions between abemaciclib and certain residues in side CDK4.</p>
Full article ">Figure 2
<p>The molecular compositions of various newly authorized anticancer drugs that specifically act on kinase families such as VEGFR, CDKs, and Flt3.</p>
Full article ">
28 pages, 1558 KiB  
Article
Network-Based Modeling of Lean Implementation Strategies and Planning in Prefabricated Construction
by Pei Dang, Linna Geng, Zhanwen Niu, Shan Jiang and Chao Sun
Buildings 2024, 14(10), 3182; https://doi.org/10.3390/buildings14103182 - 6 Oct 2024
Viewed by 209
Abstract
Abstract: Prefabricated construction (PC) is increasingly promoted in the construction sector for its potential benefits, including reduced resource assumption and improved quality. Accordingly, Lean methods are popularly applied to PC projects for optimizing operational processes and enhancing their performance in line with [...] Read more.
Abstract: Prefabricated construction (PC) is increasingly promoted in the construction sector for its potential benefits, including reduced resource assumption and improved quality. Accordingly, Lean methods are popularly applied to PC projects for optimizing operational processes and enhancing their performance in line with strategic objectives. A key factor in effectively implementing Lean to improve strategic control is developing specific strategies and planning that consider their complex interactions. Thus, this paper aims to propose a quantitative network-based model by integrating Interpretive Structural Modeling (ISM) and Matrix Impact Cross-Reference Multiplication Applied to a Classification (MICMAC) under complex network theory to develop a Lean implementation framework for effective strategy formulation. Specifically, 17 Lean implementation strategies for PC in the context of the Chinese prefabrication industry were identified via an extensive literature review and expert interviews. Then, ISM-MICMAC quantitatively identifies the direct and indirect relationships among strategies, while subsequent analysis of Topological Structure Weight (TSW) and Structural Degree Weight (SDW), as complex network parameters, is used to evaluate the importance of each strategy. The findings show that the strategic planning for Lean implementation in PC consists of four levels, i.e., foundation, organizational, technical, and control. Selecting appropriate Lean tools and technologies is crucial for PC implementation, which must be built on a top-level management team and foster a Lean culture. Moreover, it involves building a standardized system of processes and activities, enhancing both internal and external collaboration, and continuously improving processes in response to changes. On one hand, this in-depth network-based analysis offers practical insights for PC stakeholders, particularly in China, on Lean implementation in line with PC performance and strategic control and objectives. On the other hand, the network-based model can be future-implemented globally. Additionally, this study expands the current body of knowledge on Lean in PC by exploring the interrelationships of Lean implementation strategies. Full article
(This article belongs to the Special Issue Strategic Planning and Control in Complex Project Management)
15 pages, 3823 KiB  
Article
NIR Spectroscopy for the Online Monitoring of Water and Olive Oil Content in Pomace during the Extraction Process
by Alessandro Leone, Antonio Berardi, Giovanni Antonelli, Cosimo Damiano Dellisanti and Antonia Tamborrino
Appl. Syst. Innov. 2024, 7(5), 96; https://doi.org/10.3390/asi7050096 - 6 Oct 2024
Viewed by 250
Abstract
The main challenge of this scientific work was the implementation on an industrial olive oil extraction plant of an NIR device for the multispectral analysis of pomace to predict the percentage of humidity and oil contained in it. Subsequent to the implementation of [...] Read more.
The main challenge of this scientific work was the implementation on an industrial olive oil extraction plant of an NIR device for the multispectral analysis of pomace to predict the percentage of humidity and oil contained in it. Subsequent to the implementation of the NIR device on the oil extraction line on the solid’s outlet from the decanter, NIRS interaction measurements in the 761–1081 nm region were used to probe the pomace. NIRS calibration models for the prediction of water and oil content in the pomace were obtained and successfully tested and validated. The correlations of calibration results for oil and water content were 0.700 and 0.829, while the correlations of validation were 0.773 and 0.676, respectively. Low values of root mean square error were found for both the prediction and validation set. The results highlight the good robustness of an NIR approach based on a PLS calibration model to monitor the industrial olive oil process. The results obtained are a first step toward the large-scale implementation of NIR devices for monitoring pomace in oil mills. The possibility of knowing the oil lost in the pomace, moment by moment, would open a new frontier towards system control and the sustainability of the olive oil extraction process. Full article
Show Figures

Figure 1

Figure 1
<p>Layout of extraction plant: 1 defoliator, 2 hammer crushers, 3 piston pumps, 4 malaxing machines, 5 cavity pump stator, 6 horizontal centrifugal decanter, 7 vertical separator, 8 NIR probe.</p>
Full article ">Figure 2
<p>(<b>a</b>) Transmittance interface probe of the NIR tool scheme: 1 horizontal centrifugal decanter, 2 piston pumps, 3 NIR probe, 4 PC, 5 wi-fi transmitter. (<b>b</b>) Transmittance interface probe of the NIR tool photo.</p>
Full article ">Figure 3
<p>NIR spectra of the dataset in the region 850–1049 nm: (<b>a</b>) raw spectra; (<b>b</b>) spectra normalized with SNV.</p>
Full article ">Figure 4
<p>GH value for the NIR spectra of olive pomace.</p>
Full article ">Figure 5
<p>PLS cross-validation for oil content: (<b>a</b>) RMSECV vs number of components, (<b>b</b>) measured vs predicted values, (<b>c</b>) reference outliers Blue dots: measured vs predicted values, for each sample. Red cross: reference outlier sample. Dashed line: trend line of PLS model.</p>
Full article ">Figure 5 Cont.
<p>PLS cross-validation for oil content: (<b>a</b>) RMSECV vs number of components, (<b>b</b>) measured vs predicted values, (<b>c</b>) reference outliers Blue dots: measured vs predicted values, for each sample. Red cross: reference outlier sample. Dashed line: trend line of PLS model.</p>
Full article ">Figure 6
<p>Measured vs predicted values for oil content in the pomace: (<b>a</b>) calibration set; (<b>b</b>) validation set. Blue dots: measured vs predicted values for each sample. Dashed line: trend line of PLS model.</p>
Full article ">Figure 6 Cont.
<p>Measured vs predicted values for oil content in the pomace: (<b>a</b>) calibration set; (<b>b</b>) validation set. Blue dots: measured vs predicted values for each sample. Dashed line: trend line of PLS model.</p>
Full article ">Figure 7
<p>Measured vs predicted values for humidity in pomace: (<b>a</b>) calibration set; (<b>b</b>) validation set. Blue dots: measured vs predicted values for each sample. Dashed line: trend line of PLS model.</p>
Full article ">
20 pages, 1974 KiB  
Article
Modulatory Effects of Chalcone Thio-Derivatives on NF-κB and STAT3 Signaling Pathways in Hepatocellular Carcinoma Cells: A Study on Selected Active Compounds
by Katarzyna Papierska, Eliza Judasz, Wiktoria Tonińska, Maciej Kubicki and Violetta Krajka-Kuźniak
Int. J. Mol. Sci. 2024, 25(19), 10739; https://doi.org/10.3390/ijms251910739 - 5 Oct 2024
Viewed by 396
Abstract
Our previous studies demonstrated the modulatory effects of new synthetic thio-chalcone derivatives in dishes on the Nrf2, NF-κB, and STAT3 signaling pathways in colon cancer cells. This study aimed to evaluate the effect of four selected active chalcone thio-derivatives on the NF-κB and [...] Read more.
Our previous studies demonstrated the modulatory effects of new synthetic thio-chalcone derivatives in dishes on the Nrf2, NF-κB, and STAT3 signaling pathways in colon cancer cells. This study aimed to evaluate the effect of four selected active chalcone thio-derivatives on the NF-κB and STAT3 signaling pathways involved in inflammatory processes and cell proliferation in human liver cancer cells. Cell survival was assessed for cancer (HepG2) and normal (THLE-2) cell lines. Activation of NF-κB and STAT3 signaling pathways and the expression of proteins controlled by these pathways were estimated by Western blot, and qRT-PCR assessed the expression of NF-κB and STAT3 target genes. We also evaluated the impact on the selected kinases responsible for the phosphorylation of the studied transcription factors by MagneticBead-Based Multiplex Immunoassay. Among the thio-derivatives tested, especially derivatives 1 and 5, there was an impact on cell viability, cell cycle, apoptosis, and activation of NF-κB and STAT3 pathways in hepatocellular carcinoma (HCC), which confirms the possibilities of using them in combinatorial molecular targeted therapy of HCC. The tested synthetic thio-chalcones exhibit anticancer activity by initiating proapoptotic processes in HCC while showing low toxicity to non-cancerous cells. These findings confirm the possibility of using chalcone thio-derivatives in molecularly targeted combination therapy for HCC. Full article
(This article belongs to the Special Issue Advances in Cell Signaling Pathways and Signal Transduction)
Show Figures

Figure 1

Figure 1
<p>The cytotoxicity evaluation of synthetic thio-chalcone derivatives (<b>1</b>, <b>2</b>, <b>4</b>, and <b>5</b>) on: (<b>A</b>) THLE-2 cell line and (<b>B</b>) HepG2 cell line. Control cells were treated with the vehicle. The values are shown as the mean ± SEM calculated from three independent experiments. The colors and the numbers, respectively, mean the tested synthetic chalcone thio-derivatives: <b>1</b>—3-(4-methoxy-3-methylthiophenyl)-1-(3,4,5-trimethoxyphenyl)-prop-2-en-1-one. <b>2</b>—3-(3-methoxy-4-methylthiophenyl)-1-(3-bromo-4,5-dimethoxyphenyl)-prop-2-en-1-one. <b>4</b>—3-(4-methylthiophene)-1-(3-bromo-4,5-dimethoxyphenyl)-prop-2-en-1-one. <b>5</b>—3-(3-methoxy-4-methylthiophenyl)-1-(3-bromo-5-methoxy-4-methylthiophene)-prop-2-en-1-one.</p>
Full article ">Figure 2
<p>Distribution of cell cycle phases in HepG2 cell line after 24 h incubation with synthetic thio-chalcone derivatives (<b>1</b>/5, <b>2</b>/5, <b>4</b>/5, <b>5</b>/5—thio-chalcone/at a concentration of 5 μM; <b>1</b>/15, <b>2</b>/15, <b>4</b>/15, <b>5</b>/15—thio-chalcone/at a concentration of 15 μM). (<b>A</b>) Graphs of the mean ± SEM of the percentage of cells in G1/G0, S, and G2/M phases were calculated from two independent experiments. (*) indicates statistically significant differences compared to the control group for a given phase (<span class="html-italic">p</span> &lt; 0.05). (<b>B</b>) Histograms of the negative (DMSO) and positive (Topotecan 1500 nM) control analysis. (<b>C</b>) Histograms of representative samples for individual compounds.</p>
Full article ">Figure 3
<p>Apoptosis profile of HepG2 cell line treated with the synthetic thio-chalcone derivatives (<b>1</b>/5, <b>2</b>/5, <b>4</b>/5, <b>5</b>/5—thio-chalcone/at a concentration of 5 μM; <b>1</b>/15, <b>2</b>/15, <b>4</b>/15, <b>5</b>/15—thio-chalcone/at a concentration of 15 μM). (<b>A</b>) Graphs of the mean ± SEM of the percentage of apoptotic cells (in the early, late, and complete phases) after 24 h of incubation with the test compounds. Statistically significant differences compared to the control group of early apoptosis * (<span class="html-italic">p</span> &lt; 0.05) and the control group of late apoptosis # (<span class="html-italic">p</span> &lt; 0.05). (<b>B</b>) Histograms of the negative control (DMSO) and positive (Topotecan 1500 nM) analysis. (<b>C</b>) Histograms of representative samples for individual compounds. The four square markers of each graph reflect different cellular states: the top left square contains dead cells (necrosis), the top right contains late apoptosis/dead cells (cells that are positive for both Annexin V and the cell death marker 7-AAD), the left lower corner contains living cells, and the lower right corner contains early apoptosis cells (cells that are positive only for annexin V).</p>
Full article ">Figure 4
<p>Effect of the tested synthetic thio-chalcone derivatives (<b>1</b>, <b>2</b>, <b>4</b>, and <b>5</b>) in the HepG2 cell line on the protein level of: (<b>A</b>) p53 and (<b>B</b>) TNF-α.Protein levels were expressed as relative changes in the protein level with respect to the control. Representative Western blots of cytosolic fraction treated anti-p53 and anti-TNF-α antibodies are presented under the graphs. The order of the bands in the immunoblot image corresponds to the order of the bars in the diagram. Anti-β-actin antibodies were used to normalize the results. The results presented are the mean ± SEM from two separate experiments. Statistically significant differences compared to the control group * (<span class="html-italic">p</span> &lt; 0.05). See also <a href="#app1-ijms-25-10739" class="html-app">Supplementary Figure S1</a>.</p>
Full article ">Figure 5
<p>Effect of synthetic thio-chalcone derivatives (<b>1</b>, <b>2</b>, <b>4</b>, and <b>5</b>) on the regulation of protein controlling several signaling pathways measured by bead-based multiplex immunoassay in HepG2 cell line. The relative changes in the protein level of: (<b>A</b>) CREB and phospho-CREB, (<b>B</b>) JNK and phospho-JNK, (<b>C</b>) ERK and phospho-ERK, (<b>D</b>) Akt and phospho-Akt, (<b>E</b>) p38 and phospho-p38 and (<b>F</b>) p70S6K and phospho-p70S6K were measured. Results are prepared based on the cytosolic fraction of proteins and are shown in comparison to vehicle control. The values are shown as the mean ± SEM calculated from two independent experiments (a fold of control). Statistically significant differences compared to the control group * (<span class="html-italic">p</span> &lt; 0.05).</p>
Full article ">Figure 6
<p>Effect of the tested synthetic thio-chalcone derivatives (<b>1</b>, <b>2</b>, <b>4</b>, and <b>5</b>) on the protein level of: (<b>A</b>) STAT3 in cytosolic fraction from the HepG2 cell line, (<b>B</b>) STAT3 in nuclear fraction from the HepG2 cell line and (<b>C</b>) phospho-STAT3 in nuclear fraction from the HepG2 cell line. Protein levels were expressed as relative changes in the protein level with respect to the control. Representative Western blots of cytosolic fraction-treated anti-STAT3 and nuclear fraction-treated anti-STAT3 and anti-phospho-STAT3 antibodies are presented under the graphs. The order of the bands in the immunoblot image corresponds to the order of the bars in the diagram. Anti-β-actin and anti-lamin antibodies were used to normalize the results. See also <a href="#app1-ijms-25-10739" class="html-app">Supplementary Figure S2</a>. The results presented are the mean ± SEM from two separate experiments. Statistically significant differences compared to the control group * (<span class="html-italic">p</span> &lt; 0.05).</p>
Full article ">Figure 7
<p>Effect of the tested synthetic thio-chalcone derivatives (<b>1</b>, <b>2</b>, <b>4</b>, and <b>5</b>) on the expression of STAT3 and selected target genes in the HepG2 cell line: (<b>A</b>) STAT3 transcript level and (<b>B</b>) Bcl-xL and Bax transcript levels. The transcript level was calculated as the mRNA level compared to control cells, for which expression was considered. The results presented are the mean ± SEM from two separate experiments. Statistically significant differences compared to the control group * (<span class="html-italic">p</span> &lt; 0.05). (<b>C</b>) Bcl-xL and Bax protein levels. Protein levels were expressed as relative changes in the protein level with respect to the control. Representative Western blots of cytosolic fraction-treated anti-Bcl-xL and anti- Bax antibodies are presented under the graphs. The order of the bands in the immunoblot image corresponds to the order of the bars in the diagram. Anti-β-actin antibodies were used to normalize the results. See also <a href="#app1-ijms-25-10739" class="html-app">Supplementary Figure S3</a>. The results presented are the mean ± SEM from two separate experiments. Statistically significant differences compared to the control group * (<span class="html-italic">p</span> &lt; 0.05).</p>
Full article ">Figure 8
<p>Effect of the tested synthetic thio-chalcone derivatives (<b>1</b>, <b>2</b>, <b>4</b>, and <b>5</b>) on the protein level of: (<b>A</b>) NF-κB p50 and p65 subunits in cytosolic fraction from HepG2 cell line, (<b>B</b>) NF-κB p50 and p65 subunits in nuclear fraction from HepG2 cell line and (<b>C</b>) IKKα/β in cytosolic fraction from HepG2 cell line. Protein levels were expressed as relative changes in the protein level with respect to the control. Representative Western blots of cytosolic and nuclear fraction-treated anti-NF-κB p50 and anti-NF-κB p65 and cytosolic fraction-treated anti-IKKα/β antibodies are presented under the graphs. The order of the bands in the immunoblot image corresponds to the bars in the diagram. Anti-β-actin and anti-lamin antibodies were used to normalize the results. See also <a href="#app1-ijms-25-10739" class="html-app">Supplementary Figure S4</a>. The results presented are the mean ± SEM from two separate experiments. Statistically significant differences compared to the control group * (<span class="html-italic">p</span> &lt; 0.05) and compared to the BAY 11-7082 # (<span class="html-italic">p</span> &lt; 0.05).</p>
Full article ">Figure 9
<p>Effect of the tested synthetic thio-chalcone derivatives (<b>1</b>, <b>2</b>, <b>4</b>, and <b>5</b>) on the expression of NF-κB p50 and p65 subunits and selected target genes in the HepG2 cell line. (<b>A</b>) NF-κB p50 and p65 subunit transcript levels, and (<b>B</b>) COX-2 and iNOS transcript levels were measured. The transcript level was calculated as the mRNA level compared to control cells, for which expression was considered 1. The results presented are the mean ± SEM from two separate experiments. Statistically significant differences compared to the control group * (<span class="html-italic">p</span> &lt; 0.05). (<b>C</b>) COX-2 and iNOS protein levels. Protein levels were expressed as relative changes in the protein level with respect to the control. Representative Western blots of cytosolic fraction-treated anti-COX-2 and anti-iNOS antibodies are presented in the graphs. The order of the bands in the immunoblot image corresponds to the order of the bars in the diagram. Anti-β-actin antibodies were used to normalize the results. See also <a href="#app1-ijms-25-10739" class="html-app">Supplementary Figure S5</a>. The results presented are the mean ± SEM from two separate experiments. Statistically significant differences compared to the control group * (<span class="html-italic">p</span> &lt; 0.05).</p>
Full article ">
22 pages, 5864 KiB  
Article
Production Sequencing and Layout Optimization of Precast Concrete Components under Mold Resource Constraints
by Junyong Liang, Zhifang Cao, Qingzhi Zu, Hua Huang and Shunsheng Guo
Buildings 2024, 14(10), 3173; https://doi.org/10.3390/buildings14103173 - 5 Oct 2024
Viewed by 322
Abstract
Precast concrete components have attracted a lot of attention due to their efficient production on off-site production lines. However, in the precast component production process, unreasonable production sequence and mold layout will reduce production efficiency and affect the workload balance between each process. [...] Read more.
Precast concrete components have attracted a lot of attention due to their efficient production on off-site production lines. However, in the precast component production process, unreasonable production sequence and mold layout will reduce production efficiency and affect the workload balance between each process. Due to the multi-species and small-lot production characteristics of precast concrete components, the number of molds corresponding to each precast concrete component is generally limited. In this paper, a production sequence and layout optimization model for assembling precast concrete components under a limited number of molds is proposed, aiming to improve the comprehensive utilization efficiency of the mold tables and balance the workload between each production process of precast components. In order to obtain a better production sequence and a richer combination of mold layout schemes, a multi-objective teaching-learning-based optimization algorithm based on the Pareto dominance relation is developed, and an enhancement mechanism is embedded in the proposed algorithm. To verify the superior performance of the enhanced teaching-learning-based optimization algorithm in improving the comprehensive utilization efficiency of the mold tables and balancing the workload between various processes, three different sizes of precast concrete component production cases are designed. The research results show that the proposed model and optimization algorithm can help production managers to efficiently formulate more reasonable precast component production sequence and layout schemes, especially for those enterprises that are struggling to improve the efficiency of precast concrete component production. Full article
(This article belongs to the Section Construction Management, and Computers & Digitization)
Show Figures

Figure 1

Figure 1
<p>Description of production sequencing and layout problem of PCs.</p>
Full article ">Figure 2
<p>Schematic layout of two PCs on the mold table.</p>
Full article ">Figure 3
<p>The steps of the proposed ETLBO.</p>
Full article ">Figure 4
<p>A feasible encoding scheme for P14.</p>
Full article ">Figure 5
<p>A decoding scheme for the individual is encoded in <a href="#buildings-14-03173-f004" class="html-fig">Figure 4</a>.</p>
Full article ">Figure 6
<p>The teaching process of P14.</p>
Full article ">Figure 7
<p>The learning process of P14.</p>
Full article ">Figure 8
<p>The enhanced process of P14.</p>
Full article ">Figure 9
<p>Convergence and mold tables’ UR of SA, GA, TLBO, and ETLBO in P59.</p>
Full article ">Figure 10
<p>Pareto nondominated solutions obtained by ETLBO, TLBO, GA, and SA.</p>
Full article ">Figure 11
<p>Production sequencing and layout scheme with maximum <span class="html-italic">UR</span> (P192).</p>
Full article ">Figure 12
<p>Production sequencing and layout scheme with balanced <span class="html-italic">UR</span> and <span class="html-italic">SI</span> (P92).</p>
Full article ">Figure 13
<p>Production sequencing and layout scheme with minimum <span class="html-italic">SI</span> (P192).</p>
Full article ">
19 pages, 4854 KiB  
Article
Improvement of Mechanical Properties of 3D Bioprinted Structures through Cellular Overgrowth
by Adrianna Wierzbicka, Mateusz Bartniak, Jacek Grabarczyk, Nikola Biernacka, Mateusz Aftyka, Tomasz Wójcik and Dorota Bociaga
Appl. Sci. 2024, 14(19), 8977; https://doi.org/10.3390/app14198977 - 5 Oct 2024
Viewed by 506
Abstract
The common use of hydrogel materials in 3D bioprinting techniques is dictated by the unique properties of hydrogel bioinks, among which some of the most important in terms of sustaining vital cell functions in vitro in 3D cultures are the ability to retain [...] Read more.
The common use of hydrogel materials in 3D bioprinting techniques is dictated by the unique properties of hydrogel bioinks, among which some of the most important in terms of sustaining vital cell functions in vitro in 3D cultures are the ability to retain large amounts of liquid and the ability to modify rigidity and mechanical properties to reproduce the structure of the natural extracellular matrix. Due to their high biocompatibility, non-immunogenicity, and the possibility of optimizing rheological properties and bioactivity at the same time, one of the most commonly used hydrogel bioink compositions are polymer solutions based on sodium alginate and gelatin. In 3D bioprinting techniques, it is necessary for hydrogel printouts to feature an appropriate geometry to ensure proper metabolic activity of the cells contained inside the printouts. The desired solution is to obtain a thin-walled printout geometry, ensuring uniform nutrient availability and gas exchange during cultivation. Within this study’s framework, tubular bioprinted structures were developed based on sodium alginate and gelatin, containing cells of the immortalized fibroblast line NIH/3T3 in their structure. Directly after the 3D printing process, such structures are characterized by extremely low mechanical strength. The purpose of this study was to perform a comparative analysis of the viability and spreading ability of the biological material contained in the printouts during their incubation for a period of 8 weeks while monitoring the effect of cellular growth on changes in the mechanical properties of the tubular structures. The observations demonstrated that the cells contained in the 3D printouts reach the ability to grow and spread in the polymer matrix after 4 weeks of cultivation, leading to obtaining a homogeneous, interconnected cell network inside the hydrogel after 6 weeks of incubation. Analysis of the mechanical properties of the printouts indicates that with the increasing time of cultivation of the structures, the degree of their overgrowth by the biological material contained inside, and the progressive degradation of the polymer matrix process, the tensile strength of tubular 3D printouts varies. Full article
(This article belongs to the Special Issue Hydrogels and Microgels: Fundamentals, Fabrication and Applications)
Show Figures

Figure 1

Figure 1
<p>(<b>A</b>) Schematic of a 3D bioprinted structure. (<b>B</b>) Image of 3D bioprinted structure directly after the cross-linking processes.</p>
Full article ">Figure 2
<p>Schematic of the preparation of hydrogel bioinks and 3D bioprinted structures. Source: elaborated by authors using BioRender.com [<a href="#B46-applsci-14-08977" class="html-bibr">46</a>].</p>
Full article ">Figure 3
<p>(<b>A</b>) Schematic of a dedicated holder for performing static tensile tests of tubular bioprinted structures developed in the Autodesk Fusion 360 2.0.19440 x86 software (Autodesk Inc., San Francisco, CA, USA). (<b>B</b>) Photo of a tubular bioprinted structure mounted in a designed holder just before the tensile test procedure.</p>
Full article ">Figure 4
<p>Results of the evaluation of the rheological properties of polymer solutions containing no biological material and hydrogel compositions supplemented with fibroblast cells of the NIH/3T3 line.</p>
Full article ">Figure 5
<p>Results of the assessment of changes in cell viability of the immortalized fibroblasts of the NIH/3T3 line contained in the hydrogel printouts during different incubation periods of the structures.</p>
Full article ">Figure 6
<p>Summary of the results of assessing the viability and proliferation of cells contained in hydrogel printouts obtained using the live/dead assay. Arrows indicate the presence of spheroidal agglomerates. Elaborated by the authors using BioRender.com [<a href="#B46-applsci-14-08977" class="html-bibr">46</a>].</p>
Full article ">Figure 7
<p>Summary of the analysis of changes in cell morphology contained in hydrogel printouts using SEM microscopic observations. Arrows indicate the presence of spindle-shaped fibroblasts. Elaborated by authors using BioRender.com [<a href="#B46-applsci-14-08977" class="html-bibr">46</a>].</p>
Full article ">Figure 8
<p>Results of the evaluation of the changes in the mechanical properties of bioprinted hydrogel structures after their individual cultivation periods.</p>
Full article ">
24 pages, 3579 KiB  
Article
Prototype for Multi-UAV Monitoring–Control System Using WebRTC
by Fatih Kilic, Mainul Hassan and Wolfram Hardt
Drones 2024, 8(10), 551; https://doi.org/10.3390/drones8100551 - 5 Oct 2024
Viewed by 279
Abstract
Most unmanned aerial vehicle (UAV) ground control station (GCS) solutions today are either web-based or native applications, primarily designed to support a single UAV. In this paper, our research aims to provide an open, universal framework intended for rapid prototyping, addressing these objectives [...] Read more.
Most unmanned aerial vehicle (UAV) ground control station (GCS) solutions today are either web-based or native applications, primarily designed to support a single UAV. In this paper, our research aims to provide an open, universal framework intended for rapid prototyping, addressing these objectives by developing a Web Real-Time Communication (WebRTC)-based multi-UAV monitoring and control system for applications such as automated power line inspection (APOLI). The APOLI project focuses on identifying damage and faults in power line insulators through real-time image processing, video streaming, and flight data monitoring. The implementation is divided into three main parts. First, we configure UAVs for hardware-accelerated streaming using the GStreamer framework on the NVIDIA Jetson Nano companion board. Second, we develop the server-side application to receive hardware-encoded video feeds from the UAVs by utilizing a WebRTC media server. Lastly, we develop a web application that facilitates communication between clients and the server, allowing users with different authorization levels to access video feeds and control the UAVs. The system supports three user types: pilot/admin, inspector, and customer. Our research aims to leverage the WebRTC media server framework to develop a web-based GCS solution capable of managing multiple UAVs with low latency. The proposed solution enables real-time video streaming and flight data collection from multiple UAVs to a server, which is displayed in a web application interface hosted on the GCS. This approach ensures efficient inspection for applications like APOLI while prioritizing UAV safety during critical scenarios. Another advantage of the solution is its integration compatibility with platforms such as cloud services and native applications, as well as the modularity of the plugin-based architecture offered by the Janus WebRTC server for future development. Full article
(This article belongs to the Special Issue Conceptual Design, Modeling, and Control Strategies of Drones-II)
Show Figures

Figure 1

Figure 1
<p>Vision subsystem test in AREIOM Platform [<a href="#B11-drones-08-00551" class="html-bibr">11</a>].</p>
Full article ">Figure 2
<p>Streaming plugin: CPU and memory [<a href="#B32-drones-08-00551" class="html-bibr">32</a>].</p>
Full article ">Figure 3
<p>Proposed architecture.</p>
Full article ">Figure 4
<p>Hardware and software components with utilized technology.</p>
Full article ">Figure 5
<p>Flowchart of the UAV side development.</p>
Full article ">Figure 6
<p>Flowchart of the GCS side development.</p>
Full article ">Figure 7
<p>Testbed for latency measurements.</p>
Full article ">Figure 8
<p>Application interface of GCS.</p>
Full article ">Figure 9
<p>Testbed for Test 5 measurements.</p>
Full article ">Figure 10
<p>Network bandwidth during multiple streaming.</p>
Full article ">Figure 11
<p>Janus WebRTC benchmark results (9 streams).</p>
Full article ">Figure 12
<p>Janus WebRTC benchmark results − webrtc−internals dump (9 streams).</p>
Full article ">
17 pages, 4624 KiB  
Article
Metabolic Rate and Oxidative Stress as a Risk Factors in the Development of Colorectal Cancer
by Diana Sawicka, Sebastian Maciak, Anna Sadowska, Emilia Sokołowska, Sylwia Gohal, Katarzyna Guzińska-Ustymowicz, Katarzyna Niemirowicz-Laskowska and Halina Car
Int. J. Mol. Sci. 2024, 25(19), 10713; https://doi.org/10.3390/ijms251910713 - 5 Oct 2024
Viewed by 294
Abstract
There is growing evidence that the body’s energy expenditures constitute a significant risk factor for the development of most deadly diseases, including cancer. Our aim was to investigate the impact of basal metabolic rate (BMR) on the growth and progression of colorectal cancer [...] Read more.
There is growing evidence that the body’s energy expenditures constitute a significant risk factor for the development of most deadly diseases, including cancer. Our aim was to investigate the impact of basal metabolic rate (BMR) on the growth and progression of colorectal cancer (CRC). To do so, we used a unique model consisting of three lines of laboratory mice (Mus musculus) artificially selected for high (HBMR) and low (LBMR) basal metabolic rate and randomly bred individuals (non-selected, NSBMR). The experimental individuals were implanted with human colorectal cancer cells DLD-1. The variation in BMR between the lines allowed for testing the impact of whole-body metabolism on oxidative and antioxidant parameters in the liver throughout the cancerogenesis process. We investigated the dependence between metabolic values, reactive oxygen species (ROS) levels, and Kelch-like ECH-associated protein 1-based E3 ligase complexes (Keap1) gene activity in these animals. We found that the HBMR strain had a higher concentration of oxidative enzymes compared to the LBMR and NSBMR. Furthermore, the growth rate of CRC tumors was associated with alterations in the levels of oxidative stress enzymes and Keap1 expression in animals with a high metabolic rate. Our results indicate that a faster growth and development of CRC line DLD-1 is associated with enzymatic redox imbalance in animals with a high BMR. Full article
(This article belongs to the Section Molecular Oncology)
Show Figures

Figure 1

Figure 1
<p>Basal metabolic rate values (start and end) in mice divergently selected for HBMR LBMR NSBMR in two experimental groups: without CRC (−) and with CRC. The results are expressed as the mean ± SEM for each group. ** <span class="html-italic">p</span> &lt; 0.01 vs. animals without CRC (−) in each tested line, <sup>a</sup> <span class="html-italic">p</span> &lt; 0.05 vs. NSBMR start/end (−) and (CRC) end, respectively, <sup>b</sup> <span class="html-italic">p</span> &lt; 0.05 vs. LBMR start/end (−) and (CRC) end, respectively.</p>
Full article ">Figure 2
<p>Image of tumor size (<b>A</b>), tumor mass at 36 days (<b>B</b>), and tumor growth (<b>C</b>) changes in studied groups. The results are expressed as the mean ± SEM for each group. * <span class="html-italic">p</span> &lt; 0.05, <sup>a</sup> <span class="html-italic">p</span> &lt; 0.01 vs. NSBMR-CRC, <sup>b</sup> <span class="html-italic">p</span> &lt; 0.01 vs. LBMR-CRC.</p>
Full article ">Figure 3
<p>H&amp;E staining, Ki67 expression (200× magnification) (<b>A</b>) and percentage of tumor necrosis and Ki67 expression (<b>B</b>) in mice with CRC. (No tumor cells were found by H&amp;E staining in the LBMR-CRC group; therefore, a proliferation assay using the Ki67 antibody was not performed). ### <span class="html-italic">p</span> &lt; 0.001 vs. NSBMR-CRC.</p>
Full article ">Figure 4
<p>SOD, CAT, AOP, and 8-OHdG concentrations in livers of the studied animal groups. The results are presented as violin plots for each group. Differences statistically important: * <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>
Full article ">Figure 5
<p>The Pearson correlations of antioxidant/oxidative enzyme levels in livers of the studied animal groups. The results are presented as heat maps with r values for each group.</p>
Full article ">Figure 6
<p>SOD, GPx and AOPP concentrations in serum of the studied animal groups. The results are presented as violin plots for each group. Differences statistically significant: * <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>
Full article ">Figure 7
<p>TAS and TOS concentrations in serum of the studied animal groups. The results are presented as violin plots for each group. Differences statistically significant: * <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; 0.0001.</p>
Full article ">Figure 8
<p>The Pearson correlations of antioxidant/oxidative enzyme levels in serum of the studied animal groups. The results are presented as heat maps with r values for each group.</p>
Full article ">Figure 9
<p><span class="html-italic">Keap1</span> expression in livers of studied animal groups with CRC. The results are presented as log2 delta-corrected Ct values. Differences statistically significant: **** <span class="html-italic">p</span> &lt; 0.001 vs. HBMR-CRC group.</p>
Full article ">
20 pages, 1280 KiB  
Article
Establishment and Characterization of a Stable Producer Cell Line Generation Platform for the Manufacturing of Clinical-Grade Lentiviral Vectors
by Ane Arrasate, Igone Bravo, Carlos Lopez-Robles, Ane Arbelaiz-Sarasola, Maddi Ugalde, Martha Lucia Meijueiro, Miren Zuazo, Ana Valero, Soledad Banos-Mateos, Juan Carlos Ramirez, Carmen Albo, Andrés Lamsfus-Calle and Marie J. Fertin
Biomedicines 2024, 12(10), 2265; https://doi.org/10.3390/biomedicines12102265 - 4 Oct 2024
Viewed by 381
Abstract
Background/Objectives: To date, nearly 300 lentiviral-based gene therapy clinical trials have been conducted, with eight therapies receiving regulatory approval for commercialization. These advances, along with the increased number of advanced-phase clinical trials, have prompted contract development and manufacturing organizations (CDMOs) to develop innovative [...] Read more.
Background/Objectives: To date, nearly 300 lentiviral-based gene therapy clinical trials have been conducted, with eight therapies receiving regulatory approval for commercialization. These advances, along with the increased number of advanced-phase clinical trials, have prompted contract development and manufacturing organizations (CDMOs) to develop innovative strategies to address the growing demand for large-scale batches of lentiviral vectors (LVVs). Consequently, manufacturers have focused on optimizing processes under good manufacturing practices (GMPs) to improve cost-efficiency, increase process robustness, and ensure regulatory compliance. Nowadays, the LVV production process mainly relies on the transient transfection of four plasmids encoding for the lentiviral helper genes and the transgene. While this method is efficient at small scales and has also proven to be scalable, the industry is exploring alternative processes due to the high cost of GMP reagents, and the batch-to-batch variability predominantly attributed to the transfection step. Methods: Here, we report the development and implementation of a reliable and clinical-grade envisioned platform based on the generation of stable producer cell lines (SCLs) from an initial well-characterized lentiviral packaging cell line (PCL). Results: This platform enables the production of VSV-G-pseudotyped LVVs through a fully transfection-free manufacturing process. Our data demonstrate that the developed platform will facilitate successful technological transfer to large-scale LVV production for clinical application. Conclusions: With this simple and robust stable cell line generation strategy, we address key concerns associated with the costs and reproducibility of current manufacturing processes. Full article
(This article belongs to the Special Issue Gene Delivery and Gene Editing)
16 pages, 6813 KiB  
Article
Study on the Wear Performance of Surface Alloy Coating of Inner Lining Pipe under Different Load and Mineralization Conditions
by Yuntao Xi, Yucong Bi, Yang Wang, Lan Wang, Shikai Su, Lei Wang, Liqin Ding, Shanna Xu, Haitao Liu, Xinke Xiao, Ruifan Liu and Jiangtao Ji
Coatings 2024, 14(10), 1274; https://doi.org/10.3390/coatings14101274 - 4 Oct 2024
Viewed by 439
Abstract
Testing was carried out in this study to evaluate the friction and wear performance of 45# steel inner liner pipes with cladding, along with four different types of centralizing materials (45# steel, nylon, polytetrafluoroethylene (PTFE), and surface alloy coating) in oil field conditions. [...] Read more.
Testing was carried out in this study to evaluate the friction and wear performance of 45# steel inner liner pipes with cladding, along with four different types of centralizing materials (45# steel, nylon, polytetrafluoroethylene (PTFE), and surface alloy coating) in oil field conditions. Under dry-friction conditions, the coefficients of friction and rates of wear are significantly higher than their counterparts in aqueous solutions. This is attributed to the lubricating effect provided by the aqueous solution, which reduces direct friction between contact surfaces, thereby lowering wear. As the degree of mineralization in the aqueous solution increases, the coefficient of friction tends to decrease, indicating that an elevated level of mineralization enhances the lubricating properties of the aqueous solution. The wear pattern in an aqueous solution is similar to that in dry-friction conditions under different loads, but with a lower friction coefficient and wear rate. The coating has played an important role in protecting the wear process of 45# steel, and the friction coefficient and wear rate of tubing materials under various environmental media have been significantly reduced. In terms of test load, taking into account the friction coefficient and wear rate, the suggested order for centralizing materials for lining oil pipes with the surface alloy coating is as follows: (i) surface alloy coating, (ii) nylon, (iii) PTFE, and (iv) 45# steel. Full article
Show Figures

Figure 1

Figure 1
<p>Pin disc friction and wear experimental device: (<b>a</b>) schematic diagram, (<b>b</b>) physical image, and (<b>c</b>) control interface; mineralization degree aqueous solution environmental device: (<b>d</b>) schematic diagram and (<b>e</b>) physical image.</p>
Full article ">Figure 1 Cont.
<p>Pin disc friction and wear experimental device: (<b>a</b>) schematic diagram, (<b>b</b>) physical image, and (<b>c</b>) control interface; mineralization degree aqueous solution environmental device: (<b>d</b>) schematic diagram and (<b>e</b>) physical image.</p>
Full article ">Figure 2
<p>Friction coefficient of surface alloy coating of inner lining tubing material under different mineralization degrees: (<b>a</b>) cladded 45# steel inner liner pipes (disc)–45# steel (pin), (<b>b</b>) cladded 45# steel inner liner pipes (disc)–nylon (pin), (<b>c</b>) cladded 45# steel inner liner pipes (disc)–PTFE (pin), and (<b>d</b>) cladded 45# steel inner liner pipes (disc)–surface alloy coating (pin); (<b>e</b>) variation in friction coefficient of cladded 45# steel inner liner pipes with mineralization degree; variation in wear rate with different degrees of mineralization: (<b>f</b>) oil pipe material and (<b>g</b>) centralizing material.</p>
Full article ">Figure 2 Cont.
<p>Friction coefficient of surface alloy coating of inner lining tubing material under different mineralization degrees: (<b>a</b>) cladded 45# steel inner liner pipes (disc)–45# steel (pin), (<b>b</b>) cladded 45# steel inner liner pipes (disc)–nylon (pin), (<b>c</b>) cladded 45# steel inner liner pipes (disc)–PTFE (pin), and (<b>d</b>) cladded 45# steel inner liner pipes (disc)–surface alloy coating (pin); (<b>e</b>) variation in friction coefficient of cladded 45# steel inner liner pipes with mineralization degree; variation in wear rate with different degrees of mineralization: (<b>f</b>) oil pipe material and (<b>g</b>) centralizing material.</p>
Full article ">Figure 3
<p>Friction coefficient of surface-alloy-coating-lined oil pipe material under different test loads (dry friction): (<b>a</b>) cladded 45# steel inner liner pipes (disc)–45# steel (pin), (<b>b</b>) cladded 45# steel inner liner pipes (disc)–nylon (pin), (<b>c</b>) cladded 45# steel inner liner pipes (disc)–PTFE (pin), and (<b>d</b>) cladded 45# steel inner liner pipes (disc)–surface alloy coating (pin); (<b>e</b>) variation in friction coefficient of cladded 45# steel inner liner pipes with applied load (dry friction); variation in wear rate with applied load (dry friction): (<b>f</b>) oil pipe material and (<b>g</b>) centralizing material.</p>
Full article ">Figure 3 Cont.
<p>Friction coefficient of surface-alloy-coating-lined oil pipe material under different test loads (dry friction): (<b>a</b>) cladded 45# steel inner liner pipes (disc)–45# steel (pin), (<b>b</b>) cladded 45# steel inner liner pipes (disc)–nylon (pin), (<b>c</b>) cladded 45# steel inner liner pipes (disc)–PTFE (pin), and (<b>d</b>) cladded 45# steel inner liner pipes (disc)–surface alloy coating (pin); (<b>e</b>) variation in friction coefficient of cladded 45# steel inner liner pipes with applied load (dry friction); variation in wear rate with applied load (dry friction): (<b>f</b>) oil pipe material and (<b>g</b>) centralizing material.</p>
Full article ">Figure 4
<p>Friction coefficient of surface-alloy-coating-lined oil pipe material under different test loads (aqueous solution): (<b>a</b>) cladded 45# steel inner liner pipes (disc)–45# steel (pin), (<b>b</b>) cladded 45# steel inner liner pipes (disc)–nylon (pin), (<b>c</b>) cladded 45# steel inner liner pipes (disc)–PTFE (pin), and (<b>d</b>) cladded 45# steel inner liner pipes (disc)–surface alloy coating (pin); (<b>e</b>) variation in friction coefficient of cladded 45# steel inner liner pipes with applied load; variation in wear rate with applied load (30,000 mg/L mineralization-degree aqueous solution): (<b>f</b>) oil pipe material and (<b>g</b>) centralizing material.</p>
Full article ">Figure 4 Cont.
<p>Friction coefficient of surface-alloy-coating-lined oil pipe material under different test loads (aqueous solution): (<b>a</b>) cladded 45# steel inner liner pipes (disc)–45# steel (pin), (<b>b</b>) cladded 45# steel inner liner pipes (disc)–nylon (pin), (<b>c</b>) cladded 45# steel inner liner pipes (disc)–PTFE (pin), and (<b>d</b>) cladded 45# steel inner liner pipes (disc)–surface alloy coating (pin); (<b>e</b>) variation in friction coefficient of cladded 45# steel inner liner pipes with applied load; variation in wear rate with applied load (30,000 mg/L mineralization-degree aqueous solution): (<b>f</b>) oil pipe material and (<b>g</b>) centralizing material.</p>
Full article ">Figure 5
<p>SEM images of the worn surface of cladded 45# steel inner liner pipes (disc)–PTFE (pin) under different loading conditions in a 30,000 mg/L mineralization-degree aqueous solution: (<b>a</b>) cladded 45# steel inner liner pipes under 50 N, (<b>b</b>) PTFE under 50 N, (<b>c</b>) cladded 45# steel inner liner pipes under 500 N, (<b>d</b>) PTFE under 500 N, (<b>e</b>) cladded 45# steel inner liner pipes under 1000 N, (<b>f</b>) PTFE under 1000 N, (<b>g</b>) cladded 45# steel inner liner pipes under 2000 N, and (<b>h</b>) PTFE under 2000 N.</p>
Full article ">Figure 6
<p>Three-dimensional confocal microscopic images and height contour of cladded 45# steel inner liner pipes (disc)–PTFE (pin) under different loading conditions in a 30,000 mg/L mineralization-degree aqueous solution: (<b>a</b>) cladded 45# steel inner liner pipes under 50 N, (<b>b</b>) cladded 45# steel inner liner pipes under 500 N, (<b>c</b>) cladded 45# steel inner liner pipes 1000 N, (<b>d</b>) cladded 45# steel inner liner pipes under 2000 N, (<b>e</b>) PTFE under 50 N, (<b>f</b>) PTFE under 500 N, (<b>g</b>) PTFE under 500 N, (<b>h</b>) PTFE under 1000 N.</p>
Full article ">Figure 6 Cont.
<p>Three-dimensional confocal microscopic images and height contour of cladded 45# steel inner liner pipes (disc)–PTFE (pin) under different loading conditions in a 30,000 mg/L mineralization-degree aqueous solution: (<b>a</b>) cladded 45# steel inner liner pipes under 50 N, (<b>b</b>) cladded 45# steel inner liner pipes under 500 N, (<b>c</b>) cladded 45# steel inner liner pipes 1000 N, (<b>d</b>) cladded 45# steel inner liner pipes under 2000 N, (<b>e</b>) PTFE under 50 N, (<b>f</b>) PTFE under 500 N, (<b>g</b>) PTFE under 500 N, (<b>h</b>) PTFE under 1000 N.</p>
Full article ">Figure 6 Cont.
<p>Three-dimensional confocal microscopic images and height contour of cladded 45# steel inner liner pipes (disc)–PTFE (pin) under different loading conditions in a 30,000 mg/L mineralization-degree aqueous solution: (<b>a</b>) cladded 45# steel inner liner pipes under 50 N, (<b>b</b>) cladded 45# steel inner liner pipes under 500 N, (<b>c</b>) cladded 45# steel inner liner pipes 1000 N, (<b>d</b>) cladded 45# steel inner liner pipes under 2000 N, (<b>e</b>) PTFE under 50 N, (<b>f</b>) PTFE under 500 N, (<b>g</b>) PTFE under 500 N, (<b>h</b>) PTFE under 1000 N.</p>
Full article ">
15 pages, 3803 KiB  
Article
Compound K Promotes Megakaryocytic Differentiation by NLRP3 Inflammasome Activation
by Seonhwa Hwang, Min-Seo Park, Anthony Junhoe Koo, Eunsoo Yoo, Seh-Hyon Song, Hye-Kyung Kim, Min-Hi Park and Jae-Seon Kang
Biomolecules 2024, 14(10), 1257; https://doi.org/10.3390/biom14101257 - 4 Oct 2024
Viewed by 324
Abstract
Platelets are essential blood components that maintain hemostasis, prevent excessive bleeding, and facilitate wound healing. Reduced platelet counts are implicated in various diseases, including leukemia, hepatitis, cancer, and Alzheimer’s disease. Enhancing megakaryocytic differentiation is a promising strategy to increase platelet production. Compound K [...] Read more.
Platelets are essential blood components that maintain hemostasis, prevent excessive bleeding, and facilitate wound healing. Reduced platelet counts are implicated in various diseases, including leukemia, hepatitis, cancer, and Alzheimer’s disease. Enhancing megakaryocytic differentiation is a promising strategy to increase platelet production. Compound K (CK), a major bioactive metabolite of ginsenosides from Panax ginseng, has demonstrated anti-cancer and neuroprotective properties. In this study, we investigated the effects of CK on megakaryocytic differentiation and apoptosis in chronic myeloid leukemia (CML) cell lines K562 and Meg-01. CK treatment significantly upregulated the mRNA expression of key megakaryocytic differentiation markers, including CD61, CD41, and CD42a, and promoted the formation of large, multinucleated cells in K562 cells. Additionally, flow cytometry analysis revealed that CK at 5 µM induced apoptosis, a critical process in thrombocytopoiesis, in both K562 and Meg-01 cells. RT2 Profiler PCR array analysis further identified a marked increase in the expression of genes associated with the activation of the NLRP3 inflammasome in CK-treated K562 and Meg-01 cells. This study is the first to demonstrate that CK promotes megakaryocytic differentiation and apoptosis through the activation of the ERK/EGR1 and NLRP3 inflammasome pathways. These findings suggest that CK may enhance platelet production, indicating its potential as a therapeutic candidate for platelet-related disorders and other associated diseases. Full article
(This article belongs to the Special Issue Natural Bioactives as Leading Molecules for Drug Development)
Show Figures

Figure 1

Figure 1
<p>Effects of compound K (CK) on the cell growth of K562 and Meg01 cells. (<b>A</b>) The chemical structure of CK. Cell viability was measured using an MTT assay. (<b>B</b>) K562 and (<b>C</b>) Meg-01 cells were treated with vehicle (0.1% DMSO) or CK (3 or 5 µM) for 48 h or 72 h. One-way ANOVA with Bonferroni test was used to determine the significance of differences: *** <span class="html-italic">p</span> &lt; 0.001 compared to the vehicle-treated group.</p>
Full article ">Figure 2
<p>Effects of CK on the expression of megakaryocytic differentiation genes in K562 and Meg-01 cells. K562 and Meg-01 cells were treated with vehicle or CK (3 or 5 µM) for 72 h. The messenger RNA (mRNA) expression levels in (<b>A</b>) K562 and (<b>B</b>) Meg-01 cells. CK induced the secretion of differentiation markers. The protein expression of CD61, CD42a, and β-actin was measured by Western blot analysis (<span class="html-italic">n</span> = 3). Quantification results of (<b>C</b>) K562 and (<b>D</b>) Meg-01 cells and a representative blot are shown. One-way ANOVA with Bonferroni test was used to determine the significance of differences: * <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 to vehicle-treated cells. (<b>E</b>) Morphological changes of the cells and multi-lobulation of the nucleus were observed under microscope. K562 and Meg-01 cells were treated with vehicle (0.1% DMSO) or 5 µM CK for 72 h. Representative histograms are shown. Blue fluorescence indicates nuclear staining by Hoechst. Red indicates a cell membrane that has been unstained. The scale bar is 20 µm.</p>
Full article ">Figure 3
<p>Involvement of CK in the megakaryocytic differentiation-related signaling pathway-dependent gene expression activation in CML cells. Cells were treated with vehicle or CK (3 or 5 µM) for 72 h. Western blot analysis measured the levels of Egr-1, Lamin B1, phosphor-ERK (p-ERK), and ERK protein. A representative blot of (<b>A</b>) K562 and (<b>B</b>) Meg-01 cells is shown. The experiments were performed in triplicate, and the data represent the mean ± SD of independent experiments of (<b>C</b>) K562 and (<b>D</b>) Meg-01 cells. The mRNA expression levels in (<b>E</b>) K562 and (<b>F</b>) Meg-01 cells. One-way ANOVA with Bonferroni test was used to determine the significance of differences: * <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 to vehicle-treated cells.</p>
Full article ">Figure 4
<p>Effect of CK on apoptosis of K562 cells and Meg-01 cells. The population of early apoptotic (EA) and late apoptotic (LA) cells was detected using an Annexin V-FITC and propidium iodide (PI) staining kit, according to the manufacturer’s instructions. A representative histogram is shown for (<b>A</b>) K562 and (<b>B</b>) Meg-01 cells. The apoptotic cell populations in EA and LA phases were quantified. The experiments were replicated three times, and the data represent the mean ± SEM of independent experiments. One-way ANOVA with Bonferroni test was used to determine the significance of differences: ** <span class="html-italic">p</span> &lt; 0.01 and *** <span class="html-italic">p</span> &lt; 0.001 compared to vehicle-treated cells.</p>
Full article ">Figure 5
<p>Summary of the RT<sup>2</sup> Profiler PCR array analysis of the apoptosis pathway. The hierarchical clustering of gene signatures was determined using PCR arrays in (<b>A</b>) K562 cells and (<b>E</b>) Meg-01 cells. (<b>B</b>,<b>F</b>) The volcano plots identify significant changes in gene expression between groups. Cluster analysis revealed that CK upregulates the genes in (<b>C</b>) K562 and (<b>G</b>) Meg-01 cells in the positive regulation signaling pathway. (<b>D</b>,<b>H</b>) List of positive regulation-related genes regulated by CK. There is a distinct increase in the inflammasome expression among the positive regulation-related genes. Red indicates upregulation of inflammasome genes (at least 2.5-fold).</p>
Full article ">Figure 6
<p>Effects of CK on the expression of the complexes of NLRP3 inflammatory markers in K562 and Meg-01 cells. Human chronic myeloid leukemia (CML) cells were treated with vehicle or CK (3 or 5 µM) for 72 h. The protein expression of NLRP3, caspase-1, and actin was measured by Western blot analysis (<span class="html-italic">n</span> = 3). Quantification results of (<b>A</b>) K562 and (<b>B</b>) Meg-01 cells and a representative blot is shown. Also shown are the ELISA results for inflammatory cytokine IL-1ß in the vehicle or CK (3 or 5 µM) groups. IL-1β concentration was significantly increased by CK treatment in (<b>C</b>) K562 and (<b>D</b>) Meg-01 cells. The mean ± SD of three independent experiments is also shown. One-way ANOVA with Bonferroni test was used to determine the significance of differences: * <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 to vehicle-treated cells.</p>
Full article ">Figure 7
<p>Summary of the experiments on the effect of CK on megakaryocytic differentiation in CML K562 and Meg-01 cells. The observation of specific expression markers in megakaryocytic differentiation and cell morphology confirmed CK’s facilitation of differentiation. Additionally, CK reduces cell viability and promotes megakaryocytic differentiation through the activation of the NLRP3 inflammasome in human CML K562 and Meg-01 cells.</p>
Full article ">Figure A1
<p>Effects of CK on reactive oxygen species (ROS) levels. (<b>A</b>) Intracellular ROS detection was performed using fluorescence microscopy. Intracellular ROS was measured by DCFDA staining after (<b>a</b>,<b>d</b>) vehicle, (<b>b</b>,<b>e</b>) H<sub>2</sub>O<sub>2</sub>, or (<b>c</b>,<b>f</b>) 5 μM CK treatment. Representative fluorescence images of (<b>a</b>–<b>c</b>) K562 and (<b>d</b>–<b>f</b>) Meg-01 cells. The intensity of the green fluorescence indicates ROS concentration in the cells. (<b>B</b>) ROS scavenging assay after CK exposure. The effect of CK on ROS production was evaluated. ROS levels were quantitatively determined using the H<sub>2</sub>DCFDA (<span class="html-italic">n</span> = 4). Trolox was used as the positive control (P.C). (<b>C</b>) The effect of CK on peroxynitrite (ONOO<sup>−</sup>) production was evaluated (<span class="html-italic">n</span> = 4). Penicillamine was used as the P.C. The scavenging activity of CK on ROS and ONOO<sup>−</sup> induced by 10 µM SIN-1 was estimated in a cell-free in vitro culture. One-way ANOVA with Bonferroni test was used to determine the significance of differences: *** <span class="html-italic">p</span> &lt; 0.001 compared to SIN-1-treated cells. The scavenging activity of CK on ROS induced by H<sub>2</sub>O<sub>2</sub> was estimated in (<b>D</b>) K562 and (<b>E</b>) Meg-01 cells. One-way ANOVA with Bonferroni test was used to determine the significance of differences: *** <span class="html-italic">p</span> &lt; 0.001 compared to H<sub>2</sub>O<sub>2</sub>-treated cells. ### <span class="html-italic">p</span> &lt; 0.001 compared to vehicle-treated cells. “ns” represents no significant differences compared to H<sub>2</sub>O<sub>2</sub>-treated cells.</p>
Full article ">
22 pages, 4663 KiB  
Article
Investigation of the Roles of Phosphatidylinositol 4-Phosphate 5-Kinases 7,9 and Wall-Associated Kinases 1–3 in Responses to Indole-3-Carbinol and Biotic Stress in Arabidopsis Thaliana
by Hala Khamesa-Israelov, Alin Finkelstein, Eilon Shani and Daniel A. Chamovitz
Biomolecules 2024, 14(10), 1253; https://doi.org/10.3390/biom14101253 - 3 Oct 2024
Viewed by 376
Abstract
Indole-3-carbinol (I3C), a hydrolysis product of indole-3-methylglucosinolate, is toxic to herbivorous insects and pathogens. In mammals, I3C is extensively studied for its properties in cancer prevention and treatment. Produced in Brassicaceae, I3C reversibly inhibits root elongation in a concentration-dependent manner. This inhibition is [...] Read more.
Indole-3-carbinol (I3C), a hydrolysis product of indole-3-methylglucosinolate, is toxic to herbivorous insects and pathogens. In mammals, I3C is extensively studied for its properties in cancer prevention and treatment. Produced in Brassicaceae, I3C reversibly inhibits root elongation in a concentration-dependent manner. This inhibition is partially explained by the antagonistic action of I3C on auxin signaling through TIR1. To further elucidate the mode of action of I3C in plants, we have employed a forward-genetic amiRNA screen that circumvents functional redundancy. We identified and characterized two amiRNA lines with impaired I3C response. The first line, ICT2, targets the phosphatidylinositol 4-phosphate 5-kinase family (PIP5K), exhibiting tolerance to I3C, while the second line, ICS1, targets the Wall-Associated Kinases (WAK1–3) family, showing susceptibility to I3C. Both lines maintain I3C-induced antagonism of auxin signaling, indicating that their phenotypes are due to auxin-independent mechanisms. Transcript profiling experiments reveal that both lines are transcriptionally primed to respond to I3C treatment. Physiological, metabolomic, and transcriptomic analysis reveal that these kinases mediate numerous developmental processes and are involved in abiotic and biotic stress responses. Full article
(This article belongs to the Section Molecular Biology)
Show Figures

Figure 1

Figure 1
<p><span class="html-italic">ICT2</span> and <span class="html-italic">ICS1</span> are tolerant or sensitive to I3C in root growth assays. The data show the average root lengths of two sets of 30 seedlings: (<b>a</b>) <span class="html-italic">ICT2<sup>ami0</sup></span> and <span class="html-italic">ICS1<sup>ami0</sup></span>, and (<b>c</b>) <span class="html-italic">ICT2<sup>ami1</sup></span> and <span class="html-italic">ICS1<sup>ami1</sup></span> lines. These seedlings were germinated on MS with and without 500 µM I3C added. Corresponding representative seedlings are displayed in panels (<b>b</b>,<b>d</b>) for both the original and generated lines, respectively, after 14 days of growth on the aforementioned media. The scale used for panel (<b>b</b>) is 10 mm, while panel (<b>d</b>) is scaled at 5 mm. White arrows indicate root tips. The asterisk denotes a statistically significant difference between the groups, as determined by a <span class="html-italic">t</span>-test (<span class="html-italic">p</span> &lt; 0.05). (<b>e</b>) Gene expression levels of <span class="html-italic">ICT2</span> and <span class="html-italic">ICS1</span> amiRNA lines. <span class="html-italic">ICT2</span> targets PIP5K7 and PIP5K9 while <span class="html-italic">ICS1</span> targets WAK1, WAK2, and WAK3. Values are presented in log2-fold relative to WT levels. Actin was used as a standard, <span class="html-italic">n</span> = 3.</p>
Full article ">Figure 2
<p>The response in <span class="html-italic">ICT2</span> is specific to I3C. (<b>a</b>) The graph illustrates the average root lengths of 15 seedlings each of the WT, <span class="html-italic">ICT2</span>, and <span class="html-italic">ICS1</span> grown on various I3C derivatives. (<b>b</b>) Representative 7-day-old seedlings of WT, <span class="html-italic">ICS1</span>, and <span class="html-italic">ICT2</span> (displayed left to right, respectively) are shown. These seedlings were grown on different media: (<b>i</b>) Murashige and Skoog medium (MS), (<b>ii</b>) 500 µM I3C, (<b>iii</b>) 200 µM Diindolylmethane (DIM), (<b>iv</b>) 300 µM I3CxA, (<b>v</b>) 375 µM MI3CX, (<b>vi</b>) 200 nM indole-3-acetic Acid (IAA), and (<b>vii</b>) 160 µM indole-3-Acetonitrile (INA). Scale bar 10 mm. The asterisk denotes a statistically significant difference between the groups, as determined by a <span class="html-italic">t</span>-test (<span class="html-italic">p</span> &lt; 0.05). Interestingly, I3C appears to mitigate IAA-induced inhibition in both the <span class="html-italic">ICT2</span> and <span class="html-italic">ICS1</span> lines.</p>
Full article ">Figure 3
<p>Both <span class="html-italic">ICT2</span> and <span class="html-italic">ICS1</span> retain I3C inhibition of IAA signaling. WT (<b>a</b>), <span class="html-italic">ICT2</span> (<b>b</b>), and <span class="html-italic">ICS1</span> (<b>c</b>), were grown on mixtures of three concentrations of I3C (50—top row, 200—middle row, and 500 µM—bottom row) and with or without 200 nM IAA. <span class="html-italic">n</span> = 30. The asterisk denotes a statistically significant difference between the groups, as determined by a <span class="html-italic">t</span>-test (<span class="html-italic">p</span> &lt; 0.05).</p>
Full article ">Figure 4
<p>Proposed model for the effect of I3C on root elongation. I3C influences root elongations through two independent pathways. The first (<b>a</b>) is through IAA, where I3C inhibits the inhibitory effect of IAA on root elongations. In the second (<b>b</b>), I3C directly inhibits root elongation in an IAA-independent manner. <span class="html-italic">ICS1</span> potentiates this pathway (green arrow), while <span class="html-italic">ICT2</span> inhibits (red line) it. The concentration of I3C needed for the IAA-dependent pathway (<b>a</b>) is much less than the direct inhibitory pathway (<b>b</b>).</p>
Full article ">Figure 5
<p>The I3C-sensitive <span class="html-italic">ICS1</span> line contains elevated levels of endogenous I3C. Shown are the endogenous levels and uptake rates of I3C in <span class="html-italic">ICT2</span> and <span class="html-italic">ICS1</span>. (<b>a</b>) A box plot shows the endogenous levels of I3C in <span class="html-italic">ICT2</span> and <span class="html-italic">ICS1</span> and the control line <span class="html-italic">cyp79B2/B3</span>. (<b>b</b>) The box plot illustrates the amount of internal I3C following exposure to exogenous I3C in the growth medium. The amount of I3C absorbed from media was 0.21 µg\g in WT, 0.11 µg\g in <span class="html-italic">ICT2</span>, 0.003 µg\g in <span class="html-italic">ICS1</span>, and 0.39 µg\g in <span class="html-italic">cyp79B2/B3</span>. (<b>c</b>) The box plot represents the levels of Diindolylmethane (DIM), a breakdown product of I3C, for the indicated genotypes. Each box graph is annotated with an asterisk where the differences between the lines and WT are statistically significant, as determined by a <span class="html-italic">t</span>-test (<span class="html-italic">p</span> &lt; 0.05).</p>
Full article ">Figure 6
<p>Susceptibility to I3C is rescued in the double mutant <span class="html-italic">ICS1/cyp79B2/B3</span>. (<b>a</b>) The graph shows the root length for the indicated genotypes. The whisker graph compares the root lengths of <span class="html-italic">ICS1</span> and <span class="html-italic">cyp79B2/B3</span> single mutants with those of the triple mutant <span class="html-italic">ICS1/cyp79B2/B3</span>. All plants were grown on MS medium supplemented with 500 µM I3C. Asterisks denote significant differences in root length, as determined by a <span class="html-italic">t</span>-test (<span class="html-italic">p</span> &lt; 0.05). A principal component analysis of (<b>b</b>) GL profiles and (<b>c</b>) SM profiles presenting different patterns between the four tested lines and partial overlap respectively.</p>
Full article ">Figure 7
<p>Metabolites content in <span class="html-italic">ICT2</span> and <span class="html-italic">ICS1</span>. This figure visualizes the profiles of secondary metabolites in <span class="html-italic">ICT2</span> and <span class="html-italic">ICS1</span> using heat maps. The color intensity in the heat maps represents the concentration of each metabolite, with values presented in log2 scale. (<b>a</b>) This heat map displays the profile of glucosinolates (GLs) in <span class="html-italic">ICT2</span> and <span class="html-italic">ICS1</span> mutants compared to the WT. (<b>b</b>) The second heat map presents the profile of non-glucosinolate (non-GL) secondary metabolites in the same mutants relative to the WT. Data are taken from <a href="#app1-biomolecules-14-01253" class="html-app">Supplementary Table S1</a>.</p>
Full article ">Figure 8
<p>Transcriptomic analysis of the influence of I3C on gene expression in WT and I3C mutant lines. This figure provides insights into the impact of I3C on gene expression in wild type (WT) and I3C mutant lines <span class="html-italic">ICT2</span> and <span class="html-italic">ICS1</span>. (<b>a</b>) A Venn diagram illustrates the overlap between genes upregulated and downregulated in the WT, <span class="html-italic">ICT2</span>, and <span class="html-italic">ICS1</span> lines (presented in different colors) following I3C treatment. Notably, 1772 genes are commonly upregulated and 173 genes are commonly downregulated across the different lines. (<b>b</b>) A Venn diagram illustrates the overlap between misregulated genes in treated WT and untreated <span class="html-italic">ICT2</span> and <span class="html-italic">ICS1</span>, with a common 190 primed genes. (<b>c</b>) A heatmap displays the genes that are primed in the WT line treated with I3C and in the untreated <span class="html-italic">ICT2</span> and <span class="html-italic">ICS1</span> mutant lines.</p>
Full article ">Figure 9
<p>WAKs and PIP5Ks mediate abiotic stress response in Arabidopsis. This figure presents root lengths for WT, <span class="html-italic">ICT2</span>, and <span class="html-italic">ICS1</span> when exposed to different conditions. Seedlings were germinated on (<b>a</b>) standard MS medium or MS supplemented with (<b>b</b>) 500 µM I3C, (<b>c</b>) 50 mM NaCl (<b>d</b>) 1 nM H<sub>2</sub>O<sub>2</sub>, or (<b>e</b>) 200 mM Mannitol. An asterisk denotes significant differences in root length, as determined by a <span class="html-italic">t</span>-test (<span class="html-italic">p</span> &lt; 0.05), <span class="html-italic">n</span> = 30.</p>
Full article ">Figure 10
<p><span class="html-italic">ICT2</span> and <span class="html-italic">ICS1</span> are tolerant to <span class="html-italic">Pseudomonas syringae</span> infection and susceptible to <span class="html-italic">Botrytis cinerea</span>. This figure showcases the relative disease resistance and susceptibility of the <span class="html-italic">ICT2</span> and <span class="html-italic">ICS1</span> lines to specific pathogens. (<b>a</b>) A bar graph depicts the number of colonies CFU/cm<sup>2</sup> in WT, <span class="html-italic">ICT2</span>, and <span class="html-italic">ICS1</span> plants infected with <span class="html-italic">Pseudomonas syringae</span>, measured at two and four days post-infection. The asterisk denotes statistically significant differences as determined by a <span class="html-italic">t</span>-test (<span class="html-italic">p</span> &lt; 0.05). (<b>b</b>) Images represent the growth of <span class="html-italic">Pseudomonas syringae</span> colonies in WT, <span class="html-italic">ICT2</span>, and <span class="html-italic">ICS1</span> plants infected with <span class="html-italic">Pseudomonas syringae</span> at different dilutions. (<b>c</b>) A whisker chart shows the areas of necrosis measured in leaves from WT, <span class="html-italic">ICT2</span>, and <span class="html-italic">ICS1</span> four days after infection with <span class="html-italic">Botrytis cinerea</span>. * Statistical <span class="html-italic">t</span>-test, <span class="html-italic">p</span> &lt; 0.05. (<b>d</b>) Photographic representation of WT, <span class="html-italic">ICT2</span>, and <span class="html-italic">ICS1</span> leaves infected with Botrytis.</p>
Full article ">Figure 11
<p>Analysis of T-DNA mutants <span class="html-italic">wak1</span>, <span class="html-italic">wak2</span>, and <span class="html-italic">wak3</span>. Root lengths of homozygous T-DNA lines <span class="html-italic">wak1</span>, <span class="html-italic">wak2</span>, <span class="html-italic">wak3</span>, and triple knock-down line <span class="html-italic">ICS1<sup>ami0</sup></span> grown on (<b>a</b>) MS medium and on (<b>b</b>) MS medium with 500 µM I3C. * Statistical <span class="html-italic">t</span>-test, <span class="html-italic">p</span> &lt;0.05. (<b>c</b>) Representative 14-day-old seedlings grown on MS medium with 500 µM I3C, scale 0.5 mm.</p>
Full article ">Figure 12
<p>Seed abortion rate in <span class="html-italic">pip5k7</span> and <span class="html-italic">pip5k9</span>. Percentage of normal and aborted seeds in mature siliques of (<b>a</b>) <span class="html-italic">pip5k7/PIP5K7</span> and (<b>c</b>) <span class="html-italic">pip5k9/PIP5K9</span> T-DNA lines and (<b>e</b>) WT. Representative mature open siliques of (<b>b</b>) <span class="html-italic">pip5k7/PIP5K7</span>, (<b>d</b>) <span class="html-italic">pip5k9/PIP5K9</span>, and (<b>f</b>) WT. White arrows indicate undeveloped seeds. Scale bar 50 µm.</p>
Full article ">Figure 13
<p>I3C treatment affects the subcellular localization of WAK1 and WAK2. Subcellular localization of (<b>a</b>) WAK1 fused to the fluorescent marker GFP and (<b>b</b>) WAK2 fused to the fluorescent marker RFP in normal conditions (upper panel) and following I3C treatment (lower panel). The dye DAPI was used to stain the nuclei (blue).</p>
Full article ">
16 pages, 11535 KiB  
Article
Modulation of the Oncogenic LINE-1 Regulatory Network in Non-Small Cell Lung Cancer by Exosomal miRNAs
by Abeer A. I. Hassanin and Kenneth S. Ramos
Int. J. Mol. Sci. 2024, 25(19), 10674; https://doi.org/10.3390/ijms251910674 - 3 Oct 2024
Viewed by 415
Abstract
Several microRNAs (miRNAs), including miR-221-5p, Let-7b-5p, miR-21-5p, miR-9-5p, miR-126-3p, and miR-222-3p, were recently found to be enriched in circulating exosomes of patients with non-small cell lung cancers (NSCLCs). These miRNAs distinguished cancer cases from controls with high precision and were predicted to modulate [...] Read more.
Several microRNAs (miRNAs), including miR-221-5p, Let-7b-5p, miR-21-5p, miR-9-5p, miR-126-3p, and miR-222-3p, were recently found to be enriched in circulating exosomes of patients with non-small cell lung cancers (NSCLCs). These miRNAs distinguished cancer cases from controls with high precision and were predicted to modulate the expression of genes within the oncogenic LINE-1 regulatory network. To test this hypothesis, plasma exosomes from controls, early, and late-stage NSCLC patients were co-cultured with non-tumorigenic lung epithelial cells for 72 h and processed for measurements of gene expression. Exosomes from late-stage NSCLC patients markedly increased the mRNA levels of LINE-1 ORF1 and ORF2, as well as the levels of target miRNAs in naïve recipient cells compared to saline or control exosomes. Late-stage exosomes also modulated the expression of oncogenic targets within the LINE-1 regulatory network, namely, ICAM1, AGL, RGS3, RGS13, VCAM1, and TGFβ1. In sharp contrast, exosomes from controls or early-stage NSCLC patients inhibited LINE-1 expression, along with many of the genetic targets within the LINE-1 regulatory network. Thus, late-stage NSCLC exosomes activate LINE-1 and miRNA-regulated oncogenic signaling in non-tumorigenic, recipient lung bronchial epithelial cells. These findings raise important questions regarding lung cancer progression and metastasis and open the door for the exploration of new therapeutic interventions. Full article
Show Figures

Figure 1

Figure 1
<p>(<b>A-1</b>–<b>I-1</b>) Predicted genes within the LINE-1 regulatory network identified as validated targets of plasma exosomal miRNAs and their correlation scatter plots. (<b>A-1</b>) ICAM1 was a validated target for miR-21-5p, miR-146a-5p, miR-221-3p, and miR-222-3p ; (<b>B-1</b>) AGL was a validated target for let-7b-5p; (<b>C-1</b>) PKIA was a validated target for miR-210-3p ; (<b>D-1</b>) RBM39 was a validated target for miR-221-3p; (<b>E-1</b>) RGS3 was a validated target for miR-126-3p ; (<b>F-1</b>) RGS13 was a validated target for miR-146a-5p; (<b>G-1</b>) VAMP3 was a validated target for Let-7b-5p; (<b>H-1</b>) VCAM1was a validated factor for miR-126-3p; (<b>I-1</b>) TGFβ1 was a validated target for miR-21-5p and miR-146a-5p. Orange circles identify LINE-1 network genes, orange stars identify exosomal miRs, and blue squares identify regulatory miRNAs. (<b>A-2–I-2</b>) Scatter plots with Pearson correlation coefficients for the selected miRNAs and their predicted target genes (two-tailed test of significance (0.05 level). (<b>A-3–I-3</b>) Tables summarizing Pearson correlation coefficients of miRNAs and their predicted target genes.</p>
Full article ">Figure 1 Cont.
<p>(<b>A-1</b>–<b>I-1</b>) Predicted genes within the LINE-1 regulatory network identified as validated targets of plasma exosomal miRNAs and their correlation scatter plots. (<b>A-1</b>) ICAM1 was a validated target for miR-21-5p, miR-146a-5p, miR-221-3p, and miR-222-3p ; (<b>B-1</b>) AGL was a validated target for let-7b-5p; (<b>C-1</b>) PKIA was a validated target for miR-210-3p ; (<b>D-1</b>) RBM39 was a validated target for miR-221-3p; (<b>E-1</b>) RGS3 was a validated target for miR-126-3p ; (<b>F-1</b>) RGS13 was a validated target for miR-146a-5p; (<b>G-1</b>) VAMP3 was a validated target for Let-7b-5p; (<b>H-1</b>) VCAM1was a validated factor for miR-126-3p; (<b>I-1</b>) TGFβ1 was a validated target for miR-21-5p and miR-146a-5p. Orange circles identify LINE-1 network genes, orange stars identify exosomal miRs, and blue squares identify regulatory miRNAs. (<b>A-2–I-2</b>) Scatter plots with Pearson correlation coefficients for the selected miRNAs and their predicted target genes (two-tailed test of significance (0.05 level). (<b>A-3–I-3</b>) Tables summarizing Pearson correlation coefficients of miRNAs and their predicted target genes.</p>
Full article ">Figure 1 Cont.
<p>(<b>A-1</b>–<b>I-1</b>) Predicted genes within the LINE-1 regulatory network identified as validated targets of plasma exosomal miRNAs and their correlation scatter plots. (<b>A-1</b>) ICAM1 was a validated target for miR-21-5p, miR-146a-5p, miR-221-3p, and miR-222-3p ; (<b>B-1</b>) AGL was a validated target for let-7b-5p; (<b>C-1</b>) PKIA was a validated target for miR-210-3p ; (<b>D-1</b>) RBM39 was a validated target for miR-221-3p; (<b>E-1</b>) RGS3 was a validated target for miR-126-3p ; (<b>F-1</b>) RGS13 was a validated target for miR-146a-5p; (<b>G-1</b>) VAMP3 was a validated target for Let-7b-5p; (<b>H-1</b>) VCAM1was a validated factor for miR-126-3p; (<b>I-1</b>) TGFβ1 was a validated target for miR-21-5p and miR-146a-5p. Orange circles identify LINE-1 network genes, orange stars identify exosomal miRs, and blue squares identify regulatory miRNAs. (<b>A-2–I-2</b>) Scatter plots with Pearson correlation coefficients for the selected miRNAs and their predicted target genes (two-tailed test of significance (0.05 level). (<b>A-3–I-3</b>) Tables summarizing Pearson correlation coefficients of miRNAs and their predicted target genes.</p>
Full article ">Figure 1 Cont.
<p>(<b>A-1</b>–<b>I-1</b>) Predicted genes within the LINE-1 regulatory network identified as validated targets of plasma exosomal miRNAs and their correlation scatter plots. (<b>A-1</b>) ICAM1 was a validated target for miR-21-5p, miR-146a-5p, miR-221-3p, and miR-222-3p ; (<b>B-1</b>) AGL was a validated target for let-7b-5p; (<b>C-1</b>) PKIA was a validated target for miR-210-3p ; (<b>D-1</b>) RBM39 was a validated target for miR-221-3p; (<b>E-1</b>) RGS3 was a validated target for miR-126-3p ; (<b>F-1</b>) RGS13 was a validated target for miR-146a-5p; (<b>G-1</b>) VAMP3 was a validated target for Let-7b-5p; (<b>H-1</b>) VCAM1was a validated factor for miR-126-3p; (<b>I-1</b>) TGFβ1 was a validated target for miR-21-5p and miR-146a-5p. Orange circles identify LINE-1 network genes, orange stars identify exosomal miRs, and blue squares identify regulatory miRNAs. (<b>A-2–I-2</b>) Scatter plots with Pearson correlation coefficients for the selected miRNAs and their predicted target genes (two-tailed test of significance (0.05 level). (<b>A-3–I-3</b>) Tables summarizing Pearson correlation coefficients of miRNAs and their predicted target genes.</p>
Full article ">Figure 1 Cont.
<p>(<b>A-1</b>–<b>I-1</b>) Predicted genes within the LINE-1 regulatory network identified as validated targets of plasma exosomal miRNAs and their correlation scatter plots. (<b>A-1</b>) ICAM1 was a validated target for miR-21-5p, miR-146a-5p, miR-221-3p, and miR-222-3p ; (<b>B-1</b>) AGL was a validated target for let-7b-5p; (<b>C-1</b>) PKIA was a validated target for miR-210-3p ; (<b>D-1</b>) RBM39 was a validated target for miR-221-3p; (<b>E-1</b>) RGS3 was a validated target for miR-126-3p ; (<b>F-1</b>) RGS13 was a validated target for miR-146a-5p; (<b>G-1</b>) VAMP3 was a validated target for Let-7b-5p; (<b>H-1</b>) VCAM1was a validated factor for miR-126-3p; (<b>I-1</b>) TGFβ1 was a validated target for miR-21-5p and miR-146a-5p. Orange circles identify LINE-1 network genes, orange stars identify exosomal miRs, and blue squares identify regulatory miRNAs. (<b>A-2–I-2</b>) Scatter plots with Pearson correlation coefficients for the selected miRNAs and their predicted target genes (two-tailed test of significance (0.05 level). (<b>A-3–I-3</b>) Tables summarizing Pearson correlation coefficients of miRNAs and their predicted target genes.</p>
Full article ">Figure 2
<p>mRNA levels of LINE-1 and genes within its regulatory network along with their correlated miRNAs molecules in naïve BEAS-2B cells co-cultured with late-stage NSCLC plasma exosomes. (<b>A</b>) Expression of LINE-1 ORF1 (<b>A-1</b>) and ORF2 mRNAs (<b>A-2</b>). (<b>B</b>) Expression of ICAM1 mRNA (<b>B-1</b>) and four positively correlated miRNAs molecules (miR-21-5p, miR-221-3p, miR-146a-5p, and miR-222-3p) (<b>B-2</b>). (<b>C</b>) Expression of AGL (<b>C-1</b>) and Let-7b-5p (<b>C-2</b>). (<b>D</b>) Inverse correlation between PKIA mRNA (<b>D-1</b>) and miR-210-3p (<b>D-2</b>). (<b>E</b>) RBM39 gene (<b>E-1</b>) and miR-221-3p (<b>E-2</b>). (<b>F</b>) Expression of RGS3 (<b>F-1</b>) and miR-126-3p (<b>F-2</b>). (<b>G</b>) Expression of RGS13 (<b>G-1</b>) and miR-146a-5p (<b>G-2</b>). (<b>H</b>) Negative correlation between VAMP3 (<b>H-1</b>) and Let-7b-5p (<b>H-2</b>). (<b>I</b>) VCAM1 gene expression (<b>I-1</b>) and miR-126-3p (<b>I-2</b>). (<b>J</b>) TGFβ1 expression (<b>J-1</b>) and miR-21-5p and miR-146a-5p (<b>J-2</b>). PBS: BEAS-2B cells co-cultured with PBS for 72h, OH: BEAS-2B cells co-cultured with plasma exosomes from ostensibly healthy individuals for 72h, L-CAN: BEAS-2B cell co-cultured with plasma exosomes from late-stage NSCLC patients for 72h. <span class="html-italic">n</span> = 3 independent experiments and six replicates per sample. * <span class="html-italic">p</span> &lt; 0.05, ** <span class="html-italic">p</span> &lt; 0.005, *** <span class="html-italic">p</span> &lt; 0.001, **** <span class="html-italic">p</span> &lt; 0.0001.</p>
Full article ">Figure 2 Cont.
<p>mRNA levels of LINE-1 and genes within its regulatory network along with their correlated miRNAs molecules in naïve BEAS-2B cells co-cultured with late-stage NSCLC plasma exosomes. (<b>A</b>) Expression of LINE-1 ORF1 (<b>A-1</b>) and ORF2 mRNAs (<b>A-2</b>). (<b>B</b>) Expression of ICAM1 mRNA (<b>B-1</b>) and four positively correlated miRNAs molecules (miR-21-5p, miR-221-3p, miR-146a-5p, and miR-222-3p) (<b>B-2</b>). (<b>C</b>) Expression of AGL (<b>C-1</b>) and Let-7b-5p (<b>C-2</b>). (<b>D</b>) Inverse correlation between PKIA mRNA (<b>D-1</b>) and miR-210-3p (<b>D-2</b>). (<b>E</b>) RBM39 gene (<b>E-1</b>) and miR-221-3p (<b>E-2</b>). (<b>F</b>) Expression of RGS3 (<b>F-1</b>) and miR-126-3p (<b>F-2</b>). (<b>G</b>) Expression of RGS13 (<b>G-1</b>) and miR-146a-5p (<b>G-2</b>). (<b>H</b>) Negative correlation between VAMP3 (<b>H-1</b>) and Let-7b-5p (<b>H-2</b>). (<b>I</b>) VCAM1 gene expression (<b>I-1</b>) and miR-126-3p (<b>I-2</b>). (<b>J</b>) TGFβ1 expression (<b>J-1</b>) and miR-21-5p and miR-146a-5p (<b>J-2</b>). PBS: BEAS-2B cells co-cultured with PBS for 72h, OH: BEAS-2B cells co-cultured with plasma exosomes from ostensibly healthy individuals for 72h, L-CAN: BEAS-2B cell co-cultured with plasma exosomes from late-stage NSCLC patients for 72h. <span class="html-italic">n</span> = 3 independent experiments and six replicates per sample. * <span class="html-italic">p</span> &lt; 0.05, ** <span class="html-italic">p</span> &lt; 0.005, *** <span class="html-italic">p</span> &lt; 0.001, **** <span class="html-italic">p</span> &lt; 0.0001.</p>
Full article ">Figure 3
<p>mRNA levels of LINE-1 and genes within its regulatory network along with their correlated miRNAs molecules in naïve BEAS-2B cell co-cultured with early-stage NSCLC plasma exosomes. (<b>A</b>) Expression of both LINE-1 ORF1 (<b>A-1</b>) and ORF2 mRNAs (<b>A-2</b>). (<b>B</b>) Expression of ICAM1 mRNA (<b>B-1</b>) and four positively correlated miRNAs molecules (miR-21-5p, miR-221-3p, miR-146a-5p, and miR-222-3p) (<b>B-2</b>). (<b>C</b>) Expression of AGL (<b>C-1</b>) and Let-7b-5p (<b>C-2</b>). (<b>D</b>) Downregulated expression of the PKIA gene (<b>D-1</b>) and activation by miR-210-3p (<b>D-2</b>). (<b>E</b>) Expression of RBM39 gene (<b>E-1</b>) and miR-221-3p miRNA (<b>E-2</b>). (<b>F</b>) Expression of RGS3 (<b>F-1</b>) and miR-126-3p (<b>F-2</b>). (<b>G</b>) Expression of RGS13 (<b>G-1</b>) and miR-146a-5p (<b>G-2</b>). (<b>H</b>) Expression of VAMP3 (<b>H-1</b>) and Let-7b miRNA (<b>H-2</b>). (<b>I</b>) Expression of VCAM1 (<b>I-1</b>) and miR-126-3p miRNA (<b>I-2</b>). (<b>J</b>) TGFβ1 expression (<b>J-1</b>) and miRNAs miR-21-5p and miR-146a-5p (<b>J-2</b>). PBS: BEAS-2B cells co-cultured with PBS for 72h to measure basal gene expression, OH: BEAS-2B cells co-cultured with plasma exosomes from ostensibly healthy individuals for 72 h, E-CAN: BEAS-2B cells co-cultured with plasma exosomes from early-stage NSCLC patients for 72 h. <span class="html-italic">n</span> = 3 independent experiments and six replicates per sample. * <span class="html-italic">p</span> &lt; 0.05, ** <span class="html-italic">p</span> &lt; 0.005, *** <span class="html-italic">p</span> &lt; 0.001, **** <span class="html-italic">p</span> &lt; 0.0001.</p>
Full article ">Figure 3 Cont.
<p>mRNA levels of LINE-1 and genes within its regulatory network along with their correlated miRNAs molecules in naïve BEAS-2B cell co-cultured with early-stage NSCLC plasma exosomes. (<b>A</b>) Expression of both LINE-1 ORF1 (<b>A-1</b>) and ORF2 mRNAs (<b>A-2</b>). (<b>B</b>) Expression of ICAM1 mRNA (<b>B-1</b>) and four positively correlated miRNAs molecules (miR-21-5p, miR-221-3p, miR-146a-5p, and miR-222-3p) (<b>B-2</b>). (<b>C</b>) Expression of AGL (<b>C-1</b>) and Let-7b-5p (<b>C-2</b>). (<b>D</b>) Downregulated expression of the PKIA gene (<b>D-1</b>) and activation by miR-210-3p (<b>D-2</b>). (<b>E</b>) Expression of RBM39 gene (<b>E-1</b>) and miR-221-3p miRNA (<b>E-2</b>). (<b>F</b>) Expression of RGS3 (<b>F-1</b>) and miR-126-3p (<b>F-2</b>). (<b>G</b>) Expression of RGS13 (<b>G-1</b>) and miR-146a-5p (<b>G-2</b>). (<b>H</b>) Expression of VAMP3 (<b>H-1</b>) and Let-7b miRNA (<b>H-2</b>). (<b>I</b>) Expression of VCAM1 (<b>I-1</b>) and miR-126-3p miRNA (<b>I-2</b>). (<b>J</b>) TGFβ1 expression (<b>J-1</b>) and miRNAs miR-21-5p and miR-146a-5p (<b>J-2</b>). PBS: BEAS-2B cells co-cultured with PBS for 72h to measure basal gene expression, OH: BEAS-2B cells co-cultured with plasma exosomes from ostensibly healthy individuals for 72 h, E-CAN: BEAS-2B cells co-cultured with plasma exosomes from early-stage NSCLC patients for 72 h. <span class="html-italic">n</span> = 3 independent experiments and six replicates per sample. * <span class="html-italic">p</span> &lt; 0.05, ** <span class="html-italic">p</span> &lt; 0.005, *** <span class="html-italic">p</span> &lt; 0.001, **** <span class="html-italic">p</span> &lt; 0.0001.</p>
Full article ">
14 pages, 6184 KiB  
Article
FL118 Enhances Therapeutic Efficacy in Colorectal Cancer by Inhibiting the Homologous Recombination Repair Pathway through Survivin–RAD51 Downregulation
by Jungyoun Kim, Yeyeong Jeong, You Me Shin, Sung Eun Kim and Sang Joon Shin
Cancers 2024, 16(19), 3385; https://doi.org/10.3390/cancers16193385 - 3 Oct 2024
Viewed by 390
Abstract
Background/Objectives: Irinotecan, a camptothecin (CPT) derivative, is commonly used as a first-line therapy for colorectal cancer (CRC), but resistance remains a significant challenge. This study aims to explore the therapeutic potential of FL118, another CPT derivative, with a focus on overcoming resistance [...] Read more.
Background/Objectives: Irinotecan, a camptothecin (CPT) derivative, is commonly used as a first-line therapy for colorectal cancer (CRC), but resistance remains a significant challenge. This study aims to explore the therapeutic potential of FL118, another CPT derivative, with a focus on overcoming resistance to irinotecan. Methods: The effects of FL118 on CRC cells were evaluated, and bioinformatics analysis was performed on RNA-seq data. Transfection was conducted to observe the knockdown effect of survivin, and the in vivo efficacy of FL118 was assessed using a xenograft model. Results: FL118 induces apoptosis, G2/M arrest, and DNA damage. A notable mechanism of action of FL118 is a reduction in survivin levels, which downregulates the expression of RAD51, a key marker of homologous recombination, and attenuates DNA repair processes. Given that SN38 is the active metabolite of irinotecan, FL118 reduces cell viability and RAD51 in SN38-resistant LOVO cells. Conclusions: Our findings provide effective insights into the antitumor activity of FL118 and its potential as a therapeutic agent for overcoming irinotecan resistance in CRC. Full article
(This article belongs to the Section Molecular Cancer Biology)
Show Figures

Figure 1

Figure 1
<p>FL118 leads to apoptosis and G2/M cell cycle arrest. (<b>A</b>) Gene set enrichment analysis (GSEA) for FL118-treated LOVO parental cells. (<b>B</b>) The anti-apoptosis protein expression levels in LOVO and LS1034 cells treated with FL118 for 48 h were assessed using Western blot. (<b>C</b>) Cell cycle related protein levels when treating both with FL118 for 48 h, assessed by Western blot. (<b>D</b>) Cell cycle assay for flow cytometry in LOVO and LS1034 cells treated with FL118 for 48 h.</p>
Full article ">Figure 1 Cont.
<p>FL118 leads to apoptosis and G2/M cell cycle arrest. (<b>A</b>) Gene set enrichment analysis (GSEA) for FL118-treated LOVO parental cells. (<b>B</b>) The anti-apoptosis protein expression levels in LOVO and LS1034 cells treated with FL118 for 48 h were assessed using Western blot. (<b>C</b>) Cell cycle related protein levels when treating both with FL118 for 48 h, assessed by Western blot. (<b>D</b>) Cell cycle assay for flow cytometry in LOVO and LS1034 cells treated with FL118 for 48 h.</p>
Full article ">Figure 2
<p>FL118 induced double-strand breaks leading to increased p-ATM and p-γH2AX. (<b>A</b>) Comet assay after 72 h of FL118 treatment shows increased DNA damage. Data are presented as the mean ± SD. (<b>B</b>) qRT-PCR analysis shows increased mRNA levels of ATR and ATM after treatment with FL118. (<b>C</b>) p-ATM foci assay indicates increased p-ATM levels after 48 h of FL118 treatment (10 nM for LOVO and 1 nM for LS1034). (<b>D</b>) p-γH2AX foci assay demonstrates increased p-γH2AX levels after 48 h of FL118 treatment (10 nM for LOVO and 1 nM for LS1034). Statistical significance was determined using an unpaired <span class="html-italic">t</span>-test for (<b>A</b>,<b>C</b>,<b>D</b>) and ANOVA–Dunnett’s test for (<b>B</b>). Significance was as follows: * <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.</p>
Full article ">Figure 2 Cont.
<p>FL118 induced double-strand breaks leading to increased p-ATM and p-γH2AX. (<b>A</b>) Comet assay after 72 h of FL118 treatment shows increased DNA damage. Data are presented as the mean ± SD. (<b>B</b>) qRT-PCR analysis shows increased mRNA levels of ATR and ATM after treatment with FL118. (<b>C</b>) p-ATM foci assay indicates increased p-ATM levels after 48 h of FL118 treatment (10 nM for LOVO and 1 nM for LS1034). (<b>D</b>) p-γH2AX foci assay demonstrates increased p-γH2AX levels after 48 h of FL118 treatment (10 nM for LOVO and 1 nM for LS1034). Statistical significance was determined using an unpaired <span class="html-italic">t</span>-test for (<b>A</b>,<b>C</b>,<b>D</b>) and ANOVA–Dunnett’s test for (<b>B</b>). Significance was as follows: * <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.</p>
Full article ">Figure 3
<p>FL118 downregulated the homologous recombination (HR) repair gene RAD51. (<b>A</b>) DNA damage and repair pathway. (<b>B</b>) Western blot analysis for validation of the protein expression in LOVO and LS1034 cells treated with FL118 for 48 h. (<b>C</b>) qRT-PCR for RAD51 expression in LOVO and LS1034 cells treated with 1–100 nM FL118 for 48 h. Statistical value was determined by ANOVA–Tukey’s test. (<b>D</b>) RAD51 foci assay after treatment with FL118 for 48 h in LOVO and LS1034 cells. Statistical value was determined by an unpaired <span class="html-italic">t</span>-test. Significance was as follows: * <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.</p>
Full article ">Figure 4
<p>FL118-induced survivin inhibition affected RAD51. (<b>A</b>) Correlation of gene expression between BIRC5 and HR-repair-related genes (RAD51, BRCA1, EME1, and EXO1). Pearson’s correlation coefficient and the <span class="html-italic">p</span>-value are above each figure. (<b>B</b>) Survivin and RAD51 mRNA levels under transfection with si-survivin for 48 h. Statistical values were determined by ANOVA followed by Dunnett’s tests. Significance was as follows: * <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. (<b>C</b>) Western blot analysis of LOVO and LS1034 cells treated with si-survivin for 48 h. (<b>D</b>) Western blot analysis of LOVO and LS1034 cells treated with si-RAD51 for 48 h. (<b>E</b>) Western blot analysis of SW620 and COLO201 cells treated with FL118 and (<b>F</b>) transected with si-survivin for 48 h. (<b>G</b>) Combenefit HSA score for estimating the synergistic effect between FL118 and olaparib treatment for 48 h in the LOVO, LS1034, SW620, and COLO201 cell lines.</p>
Full article ">Figure 5
<p>FL118 overcomes SN38 resistance by inhibiting the HR repair pathway. (<b>A</b>) IC50 values for FL118 and SN38, analyzed by CCK-8 assay. (<b>B</b>) GSEA pathway analysis, (<b>C</b>) volcano plot, and (<b>D</b>) heatmap for parental LOVO cells treated with FL118 and SN38. (<b>E</b>) CCK-8 assay of FL118 and SN38 in SN38-resistant LOVO cells. (<b>F</b>) Dot plot for enriched pathway analysis of SN38-resistant LOVO cells treated with FL118. (<b>G</b>) Western blot analysis of SN38-resistant LOVO cells treated with FL118 and SN38 for 48 h.</p>
Full article ">Figure 5 Cont.
<p>FL118 overcomes SN38 resistance by inhibiting the HR repair pathway. (<b>A</b>) IC50 values for FL118 and SN38, analyzed by CCK-8 assay. (<b>B</b>) GSEA pathway analysis, (<b>C</b>) volcano plot, and (<b>D</b>) heatmap for parental LOVO cells treated with FL118 and SN38. (<b>E</b>) CCK-8 assay of FL118 and SN38 in SN38-resistant LOVO cells. (<b>F</b>) Dot plot for enriched pathway analysis of SN38-resistant LOVO cells treated with FL118. (<b>G</b>) Western blot analysis of SN38-resistant LOVO cells treated with FL118 and SN38 for 48 h.</p>
Full article ">Figure 6
<p>In vivo study of treating LOVO cell xenografts with FL118. (<b>A</b>) Tumor volume and (<b>B</b>) dot plot for tumor weight in LOVO cell-injected nude mice. (<b>C</b>) Image of LOVO cell xenograft tumors at the end of the experiment. (<b>D</b>) Tumor volume and (<b>E</b>) dot plot for tumor weight in SN38-resistant LOVO cell-injected nude mice. (<b>F</b>) Image of SN38-resistant LOVO cell xenograft tumors at the end of the experiment. Statistical values were determined by ANOVA–Tukey’s test. Data are presented as the mean ± SEM. Significance was as follows: * <span class="html-italic">p</span> &lt; 0.05 and ** <span class="html-italic">p</span> &lt; 0.01.</p>
Full article ">
Back to TopTop