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Search Results (34,861)

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24 pages, 1902 KiB  
Review
Unraveling the Role of Ubiquitin-Conjugating Enzyme UBE2T in Tumorigenesis: A Comprehensive Review
by Chang Gao, Yan-Jun Liu, Jing Yu, Ran Wang, Jin-Jin Shi, Ru-Yi Chen, Guan-Jun Yang and Jiong Chen
Cells 2025, 14(1), 15; https://doi.org/10.3390/cells14010015 (registering DOI) - 26 Dec 2024
Abstract
Ubiquitin-conjugating enzyme E2 T (UBE2T) is a crucial E2 enzyme in the ubiquitin-proteasome system (UPS), playing a significant role in the ubiquitination of proteins and influencing a wide range of cellular processes, including proliferation, differentiation, apoptosis, invasion, and metabolism. Its overexpression has been [...] Read more.
Ubiquitin-conjugating enzyme E2 T (UBE2T) is a crucial E2 enzyme in the ubiquitin-proteasome system (UPS), playing a significant role in the ubiquitination of proteins and influencing a wide range of cellular processes, including proliferation, differentiation, apoptosis, invasion, and metabolism. Its overexpression has been implicated in various malignancies, such as lung adenocarcinoma, gastric cancer, pancreatic cancer, liver cancer, and ovarian cancer, where it correlates strongly with disease progression. UBE2T facilitates tumorigenesis and malignant behaviors by mediating essential functions such as DNA repair, apoptosis, cell cycle regulation, and the activation of oncogenic signaling pathways. High levels of UBE2T expression are associated with poor survival outcomes, highlighting its potential as a molecular biomarker for cancer prognosis. Increasing evidence suggests that UBE2T acts as an oncogene and could serve as a promising therapeutic target in cancer treatment. This review aims to provide a detailed overview of UBE2T’s structure, functions, and molecular mechanisms involved in cancer progression as well as recent developments in UBE2T-targeted inhibitors. Such insights may pave the way for novel strategies in cancer diagnosis and treatment, enhancing our understanding of UBE2T’s role in cancer biology and supporting the development of innovative therapeutic approaches. Full article
40 pages, 1014 KiB  
Review
Advancements in Antioxidant-Based Therapeutics for Spinal Cord Injury: A Critical Review of Strategies and Combination Approaches
by Yang-Jin Shen, Yin-Cheng Huang and Yi-Chuan Cheng
Antioxidants 2025, 14(1), 17; https://doi.org/10.3390/antiox14010017 (registering DOI) - 26 Dec 2024
Abstract
Spinal cord injury (SCI) initiates a cascade of secondary damage driven by oxidative stress, characterized by the excessive production of reactive oxygen species and other reactive molecules, which exacerbate cellular and tissue damage through the activation of deleterious signaling pathways. This review provides [...] Read more.
Spinal cord injury (SCI) initiates a cascade of secondary damage driven by oxidative stress, characterized by the excessive production of reactive oxygen species and other reactive molecules, which exacerbate cellular and tissue damage through the activation of deleterious signaling pathways. This review provides a comprehensive and critical evaluation of recent advancements in antioxidant-based therapeutic strategies for SCI, including natural compounds, RNA-based therapies, stem cell interventions, and biomaterial applications. It emphasizes the limitations of single-regimen approaches, particularly their limited efficacy and suboptimal delivery to injured spinal cord tissue, while highlighting the synergistic potential of combination therapies that integrate multiple modalities to address the multifaceted pathophysiology of SCI. By analyzing emerging trends and current limitations, this review identifies key challenges and proposes future directions, including the refinement of antioxidant delivery systems, the development of multi-targeted approaches, and strategies to overcome the structural complexities of the spinal cord. This work underscores the pressing need for innovative and integrative therapeutic approaches to advance the clinical translation of antioxidant-based interventions and improve outcomes for SCI patients. Full article
21 pages, 3014 KiB  
Review
The Role of Pentacyclic Triterpenoids in Non-Small Cell Lung Cancer: The Mechanisms of Action and Therapeutic Potential
by Young-Shin Lee, Ryuk Jun Kwon, Hye Sun Lee, Jae Heun Chung, Yun Seong Kim, Han-Sol Jeong, Su-Jung Park, Seung Yeon Lee, Taehwa Kim and Seong Hoon Yoon
Pharmaceutics 2025, 17(1), 22; https://doi.org/10.3390/pharmaceutics17010022 (registering DOI) - 26 Dec 2024
Abstract
Lung cancer remains a major global health problem because of its high cancer-related mortality rate despite advances in therapeutic approaches. Non-small cell lung cancer (NSCLC), a major subtype of lung cancer, is more amenable to surgical intervention in its early stages. However, the [...] Read more.
Lung cancer remains a major global health problem because of its high cancer-related mortality rate despite advances in therapeutic approaches. Non-small cell lung cancer (NSCLC), a major subtype of lung cancer, is more amenable to surgical intervention in its early stages. However, the prognosis for advanced NSCLC remains poor, owing to limited treatment options. This underscores the growing need for novel therapeutic strategies to complement existing treatments and improve patient outcomes. In recent years, pentacyclic triterpenoids, a group of natural compounds, have emerged as promising candidates for cancer therapy due to their anticancer properties. Pentacyclic triterpenoids, such as lupeol, betulinic acid, betulin, oleanolic acid, ursolic acid, glycyrrhetinic acid, glycyrrhizin, and asiatic acid, have demonstrated the ability to inhibit cell proliferation and angiogenesis, induce apoptosis, suppress metastasis, and modulate inflammatory and immune pathways in NSCLC cell line models. These compounds exert their effects by modulating important signaling pathways such as NF-κB, PI3K/Akt, and MAPK. Furthermore, advances in drug delivery technologies such as nanocarriers and targeted delivery systems have improved the bioavailability and therapeutic efficacy of triterpenoids. However, despite promising preclinical data, rigorous clinical trials are needed to verify their safety and efficacy. This review explores the role of triterpenoids in NSCLC and therapeutic potential in preclinical models, focusing on their molecular mechanisms of action. Full article
(This article belongs to the Special Issue Natural Products for Anticancer Application)
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<p>Structure of pentacyclic triterpenoids.</p>
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<p>Overview of molecular mechanism of pentacyclic triterpenoids in NSCLC.</p>
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<p>Apoptosis induction by pentacyclic triterpenoids.</p>
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<p>Inhibition of proliferation and cell growth by pentacyclic triterpenoids.</p>
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<p>Inhibition of angiogenesis by pentacyclic triterpenoids.</p>
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<p>Anti-metastatic effects of pentacyclic triterpenoids.</p>
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<p>Modulation of inflammatory pathways by pentacyclic triterpenoids.</p>
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<p>Immune modulation by pentacyclic triterpenoids.</p>
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21 pages, 836 KiB  
Review
Exploring the Structural Diversity and Biotechnological Potential of the Rhodophyte Phycolectome
by Éllen F. Rodrigues, Flavia Alves Verza, Felipe Garcia Nishimura, Renê Oliveira Beleboni, Cedric Hermans, Kaat Janssens, Maarten Lieven De Mol, Paco Hulpiau and Mozart Marins
Mar. Drugs 2025, 23(1), 8; https://doi.org/10.3390/md23010008 (registering DOI) - 26 Dec 2024
Abstract
Lectins are non-covalent glycan-binding proteins found in all living organisms, binding specifically to carbohydrates through glycan-binding domains. Lectins have various biological functions, including cell signaling, molecular recognition, and innate immune responses, which play multiple roles in the physiological and developmental processes of organisms. [...] Read more.
Lectins are non-covalent glycan-binding proteins found in all living organisms, binding specifically to carbohydrates through glycan-binding domains. Lectins have various biological functions, including cell signaling, molecular recognition, and innate immune responses, which play multiple roles in the physiological and developmental processes of organisms. Moreover, their diversity enables biotechnological exploration as biomarkers, biosensors, drug-delivery platforms, and lead molecules for anticancer, antidiabetic, and antimicrobial drugs. Lectins from Rhodophytes (red seaweed) have been extensively reported and characterized for their unique molecular structures, carbohydrate-binding specificities, and important biological activities. The increasing number of sequenced Rhodophyte genomes offers the opportunity to further study this rich source of lectins, potentially uncovering new ones with properties significantly different from their terrestrial plant counterparts, thus opening new biotechnological applications. We compiled literature data and conducted an in-depth analysis of the phycolectomes from all Rhodophyta genomes available in NCBI datasets. Using Hidden Markov Models capable of identifying lectin-type domains, we found at least six different types of lectin domains present in Rhodophytes, demonstrating their potential in identifying new lectins. This review integrates a computational analysis of the Rhodophyte phycolectome with existing information on red algae lectins and their biotechnological potential. Full article
5 pages, 1416 KiB  
Proceeding Paper
Inhibition of Migration of SW-480 Cells Induced by Royal Jelly Due to Reduction of β-Catenin
by Milena Jovanović and Dragana Šeklić
Biol. Life Sci. Forum 2024, 40(1), 5; https://doi.org/10.3390/blsf2024040005 - 26 Dec 2024
Abstract
Royal jelly (RJ), a natural bee product known for its abundance of bioactive compounds, is often referred to as a “superfood” and has been utilized in alternative medicine for centuries. Numerous studies have highlighted its therapeutic properties, including anticancer activity. A major challenge [...] Read more.
Royal jelly (RJ), a natural bee product known for its abundance of bioactive compounds, is often referred to as a “superfood” and has been utilized in alternative medicine for centuries. Numerous studies have highlighted its therapeutic properties, including anticancer activity. A major challenge in standard cancer therapy is the migration of cancer cells, which leads to metastasis and the formation of secondary tumors with often fatal outcomes. Cancer cell migration is facilitated by the epithelial-to-mesenchymal transition (EMT) and the aberrant activation of the Wnt/β-catenin signaling pathway. A key component of this pathway, the transcription factor β-catenin, regulates the expression of various cellular components that play critical roles in cell motility. This study investigated the antimigratory potential of RJ on the colorectal cancer cell line SW-480 and its effects on β-catenin protein expression. RJ significantly suppressed the motility of SW-480 cells and markedly reduced β-catenin protein levels 24 h after treatment. These findings underscore the potential of RJ as a functional food to regulate colorectal cancer cell motility through modulation of β-catenin, thereby reducing disease aggressiveness. Full article
(This article belongs to the Proceedings of The 5th International Electronic Conference on Foods)
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<p>Representative micrographs showing the migratory potential of control and SW-480 cells treated with RJ (<b>a</b>). Results are also presented as mean values ± standard error from two independent experiments performed in triplicate (<b>b</b>); * <span class="html-italic">p</span> &lt; 0.05 is considered as statistically significant differences between treatments and control values and # <span class="html-italic">p</span> &lt; 0.05 is considered as statistically significant differences between treatment concentrations. Scale bar: 30 µm.</p>
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<p>Representative micrographs showing β-catenin protein expression and localization (<b>a</b>) and relative fluorescence intensity (<b>b</b>) in untreated and SW-480 cells treated with RJ. Results are presented as mean ± standard error from 2 independent experiments performed in triplicate, where * <span class="html-italic">p</span> &lt; 0.05 is considered as statistically significant differences between treatments and control values and # <span class="html-italic">p</span> &lt; 0.05 is considered as statistically significant differences between treatment concentrations. Scale bar: 50 µm.</p>
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16 pages, 1848 KiB  
Article
Hypoxia Regulates Brown Adipocyte Differentiation and Stimulates miR-210 by HIF-1α
by Jan Caca, Alexander Bartelt and Virginia Egea
Int. J. Mol. Sci. 2025, 26(1), 117; https://doi.org/10.3390/ijms26010117 (registering DOI) - 26 Dec 2024
Abstract
MicroRNAs (miRNAs) are short sequences of single-stranded non-coding RNAs that target messenger RNAs, leading to their repression or decay. Interestingly, miRNAs play a role in the cellular response to low oxygen levels, known as hypoxia, which is associated with reactive oxygen species and [...] Read more.
MicroRNAs (miRNAs) are short sequences of single-stranded non-coding RNAs that target messenger RNAs, leading to their repression or decay. Interestingly, miRNAs play a role in the cellular response to low oxygen levels, known as hypoxia, which is associated with reactive oxygen species and oxidative stress. However, the physiological implications of hypoxia-induced miRNAs (“hypoxamiRs”) remain largely unclear. Here, we investigate the role of miR-210 in brown adipocyte differentiation and thermogenesis. We treated the cells under sympathetic stimulation with hypoxia, CoCl2, or IOX2. To manipulate miR-210, we performed reverse transfection with antagomiRs. Adipocyte markers expression, lipid accumulation, lipolysis, and oxygen consumption were measured. Hypoxia hindered BAT differentiation and suppressed sympathetic stimulation. Hypoxia-induced HIF-1α stabilization increased miR-210 in brown adipocytes. Interestingly, miR-210-5p enhanced differentiation under normoxic conditions but was insufficient to rescue the inhibition of brown adipocyte differentiation under hypoxic conditions. Although adrenergic stimulation activated HIF-1α signaling and upregulated miR-210 expression, inhibition of miR-210-5p did not significantly influence UCP1 expression or oxygen consumption. In summary, hypoxia and adrenergic stimulation upregulated miR-210, which impacted brown adipocyte differentiation and thermogenesis. These findings offer new insights for the physiological role of hypoxamiRs in brown adipose tissue, which could aid in understanding oxidative stress and treatment of metabolic disorders. Full article
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<p>Hypoxia and HIF-1α stabilization regulate miR-210 expression in brown adipocytes. (<b>A</b>) Western blotting analysis of HIF-1α protein expression in immortalized brown adipocytes exposed to normoxic (N) or hypoxic conditions (H) or treated with IOX2 (100 µM) and CoCl<sub>2</sub> (100 µM) under normoxic conditions for 24 h. (<b>B</b>) Subcellular localization of HIF-1α was examined by immunocytochemistry analysis under normoxic conditions (Control), hypoxic conditions for 12 h, or by incubation with IOX-2 (100 µM) for 3 h. Scale bars 100 µm. (<b>C</b>) qPCR analysis of HIF-1α target genes after incubation of brown adipocytes under normoxic (N) or hypoxic conditions (H) for 12 h. (<b>D</b>) Immortalized brown adipocytes were transfected with either negative control siRNA (NC) or HIF-1α siRNA (KD) 2 days prior to the assay. Subsequently, the cells were exposed to normoxic (N) or hypoxic conditions (H) or treated with IOX2 (100 µM) and CoCl<sub>2</sub> (100 µM) under normoxic conditions for 24 h. After 24 h, RNA was collected and subjected to quantification of miR-210-3p and -5p expression using qPCR analysis. The miRNA levels were normalized to sno202. The data represent the mean ± SD (n = 3); Statistical significance is when * <span class="html-italic">p</span> &lt; 0.05, ** <span class="html-italic">p</span> &lt; 0.01, *** <span class="html-italic">p</span> &lt; 0.001.</p>
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<p>Hypoxia impairs brown adipocyte differentiation. (<b>A</b>) Microscopic analysis of immortalized brown adipocytes differentiated under normoxic (N) or hypoxic conditions (H). (<b>B</b>) Immunoblot analysis of PDGFRα and β-Tubulin in undifferentiated (U) and differentiated brown adipocytes (D) cultured under normoxic (N) or hypoxic conditions (H) for 24 h. (<b>C</b>) Immunofluorescence analysis of PDGFRα (red) and DAPI (blue) of immortalized brown adipocytes differentiated under normoxic (N) or hypoxic conditions (H). (<b>D</b>) qPCR for adipogenic markers of immortalized brown adipocytes transfected with either negative control siRNA (NC) or LNA miR-210-5p inhibitor (I) and differentiated under normoxic (N) or hypoxic conditions (H) for 5 days. (<b>E</b>) Cell staining with Oil Red O for adipogenic differentiation after 5 days of differentiation under normoxic (N) or hypoxic (H) conditions is shown by representative microscopic images of stained cellular monolayers. (<b>F</b>) Oil Red O spectrophotometry by Tecan plate reader and stain recovery after extraction from the cells. (<b>G</b>) Bodipy staining analysis of immortalized brown adipocytes transfected with either negative control miRNA (NC) or LNA miR-210-5p-mimic (M) and -inhibitor (I) after differentiation under normoxic (N) or hypoxic conditions (H). Data shown represent the mean ± SD of triplicate measurements (n = 3). Stadistical significance when * <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. Scale bars 100 µm.</p>
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<p>Hypoxia impairs the thermogenic capacity of brown adipocytes. (<b>A</b>) qPCR analysis of <span class="html-italic">Ucp-1</span> in primary brown adipocytes transfected with either control miRNA (NC) or LNA miR-210-5p inhibitor (I) and treated under normoxic or hypoxic conditions with or without CL (1 µM) for a duration of 4 h. (<b>B</b>) qPCR of <span class="html-italic">Ppargc1a</span>, <span class="html-italic">Elovl3</span>, and <span class="html-italic">Cd36</span> in primary brown adipocytes transfected with either negative control miRNA (NC) or LNA miR-210-5p inhibitor (I) and treated under normoxic or hypoxic conditions with or without CL (1 µM) for a duration of 4 h. (<b>C</b>,<b>D</b>) Oxygen consumption rates in negative control miRNA (NC) and LNA miR-210-5p inhibitor (I) transfected brown adipocytes in the presence or absence of IOX-2 (100 µM) for 2 h and normalized to protein content. Data shown represent the mean ± SD of triplicate measurements (n = 5). Stadistical significance when * <span class="html-italic">p</span> &lt; 0.05; ** <span class="html-italic">p</span> &lt; 0.01; *** <span class="html-italic">p</span> &lt; 0.001.</p>
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<p>Adrenergic stimuli activate HIF-1α signaling, leading to an increase in miR-210 expression. (<b>A</b>) Immunoblot analysis of HIF-1α in immortalized brown adipocytes after exposure to NE (1 µM) and CL (1 µM) for 2, 4, 8, or 24 hours. (<b>B</b>) qPCR analysis of miR-210-3p and -5p expression after 4 and 24 h incubation with NE (1 µM) and CL (1 µM). (<b>C</b>) qPCR analysis of <span class="html-italic">Ucp-1.</span> (<b>D</b>) Immunoblot analysis of UCP-1, Electron Transport Chain Complexes, and β-tubulin in immortalized brown adipocytes after transfection with (0, 20, 40, or 80) nM of miR-210-5p inhibitor with or without CL (1 µM) stimulation. (<b>E</b>) Oxygen consumption rate of transfected adipocytes (<b>F</b>) Quantification of glycerol concentration of transfected brown adipocytes 6 h after incubation with either NE or CL (1 µM). Data shown represent the mean ± SD of triplicate measurements (n = 3). Stadistical significance when *** <span class="html-italic">p</span> &lt; 0.001.</p>
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22 pages, 13566 KiB  
Article
In Silico Analysis Revealed Marco (SR-A6) and Abca1/2 as Potential Regulators of Lipid Metabolism in M1 Macrophage Hysteresis
by Yubo Zhang, Wenbo Yang, Yutaro Kumagai, Martin Loza, Yitao Yang, Sung-Joon Park and Kenta Nakai
Int. J. Mol. Sci. 2025, 26(1), 111; https://doi.org/10.3390/ijms26010111 (registering DOI) - 26 Dec 2024
Abstract
Macrophages undergo polarization, resulting in distinct phenotypes. These transitions, including de-/repolarization, lead to hysteresis, where cells retain genetic and epigenetic signatures of previous states, influencing macrophage function. We previously identified a set of interferon-stimulated genes (ISGs) associated with high lipid levels in macrophages [...] Read more.
Macrophages undergo polarization, resulting in distinct phenotypes. These transitions, including de-/repolarization, lead to hysteresis, where cells retain genetic and epigenetic signatures of previous states, influencing macrophage function. We previously identified a set of interferon-stimulated genes (ISGs) associated with high lipid levels in macrophages that exhibited hysteresis following M1 polarization, suggesting potential alterations in lipid metabolism. In this study, we applied weighted gene co-expression network analysis (WGCNA) and conducted comparative analyses on 162 RNA-seq samples from de-/repolarized and lipid-loaded macrophages, followed by functional exploration. Our results demonstrate that during M1 hysteresis, the sustained high expression of Marco (SR-A6) enhances lipid uptake, while the suppression of Abca1/2 reduces lipid efflux, collectively leading to elevated intracellular lipid levels. This accumulation may compensate for reduced cholesterol biosynthesis and provide energy for sustained inflammatory responses and interferon signaling. Our findings elucidate the relationship between M1 hysteresis and lipid metabolism, contributing to understanding the underlying mechanisms of macrophage hysteresis. Full article
(This article belongs to the Section Molecular Immunology)
23 pages, 1210 KiB  
Review
The Hippo Signaling Pathway Manipulates Cellular Senescence
by Chiharu Miyajima, Mai Nagasaka, Hiromasa Aoki, Kohki Toriuchi, Shogo Yamanaka, Sakura Hashiguchi, Daisuke Morishita, Mineyoshi Aoyama, Hidetoshi Hayashi and Yasumichi Inoue
Cells 2025, 14(1), 13; https://doi.org/10.3390/cells14010013 (registering DOI) - 26 Dec 2024
Abstract
The Hippo pathway, a kinase cascade, coordinates with many intracellular signals and mediates the regulation of the activities of various downstream transcription factors and their coactivators to maintain homeostasis. Therefore, the aberrant activation of the Hippo pathway and its associated molecules imposes significant [...] Read more.
The Hippo pathway, a kinase cascade, coordinates with many intracellular signals and mediates the regulation of the activities of various downstream transcription factors and their coactivators to maintain homeostasis. Therefore, the aberrant activation of the Hippo pathway and its associated molecules imposes significant stress on tissues and cells, leading to cancer, immune disorders, and a number of diseases. Cellular senescence, the mechanism by which cells counteract stress, prevents cells from unnecessary damage and leads to sustained cell cycle arrest. It acts as a powerful defense mechanism against normal organ development and aging-related diseases. On the other hand, the accumulation of senescent cells without their proper removal contributes to the development or worsening of cancer and age-related diseases. A correlation was recently reported between the Hippo pathway and cellular senescence, which preserves tissue homeostasis. This review is the first to describe the close relationship between aging and the Hippo pathway, and provides insights into the mechanisms of aging and the development of age-related diseases. In addition, it describes advanced findings that may lead to the development of tissue regeneration therapies and drugs targeting rejuvenation. Full article
(This article belongs to the Special Issue The Role of Cellular Senescence in Health, Disease, and Aging)
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<p>Effects of the Hippo pathway on cellular senescence [<a href="#B30-cells-14-00013" class="html-bibr">30</a>,<a href="#B31-cells-14-00013" class="html-bibr">31</a>,<a href="#B34-cells-14-00013" class="html-bibr">34</a>,<a href="#B35-cells-14-00013" class="html-bibr">35</a>,<a href="#B37-cells-14-00013" class="html-bibr">37</a>,<a href="#B38-cells-14-00013" class="html-bibr">38</a>,<a href="#B40-cells-14-00013" class="html-bibr">40</a>,<a href="#B44-cells-14-00013" class="html-bibr">44</a>,<a href="#B47-cells-14-00013" class="html-bibr">47</a>,<a href="#B51-cells-14-00013" class="html-bibr">51</a>,<a href="#B53-cells-14-00013" class="html-bibr">53</a>]. Factors associated with the Hippo pathway contribute to cellular senescence by regulating a number of molecules. MST1/2 and LATS1/2 promote senescence, whereas YAP/TAZ promote and inhibit senescence depending on the molecules associated. TEAD contributes to the expression of molecules that inhibit senescence. Arrows and perpendicular bars indicate potentiating and inhibitory effects.</p>
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<p>Regulation of SASP factor expression by the Hippo pathway [<a href="#B23-cells-14-00013" class="html-bibr">23</a>,<a href="#B25-cells-14-00013" class="html-bibr">25</a>,<a href="#B94-cells-14-00013" class="html-bibr">94</a>,<a href="#B95-cells-14-00013" class="html-bibr">95</a>,<a href="#B96-cells-14-00013" class="html-bibr">96</a>,<a href="#B97-cells-14-00013" class="html-bibr">97</a>,<a href="#B98-cells-14-00013" class="html-bibr">98</a>,<a href="#B104-cells-14-00013" class="html-bibr">104</a>,<a href="#B105-cells-14-00013" class="html-bibr">105</a>,<a href="#B106-cells-14-00013" class="html-bibr">106</a>,<a href="#B107-cells-14-00013" class="html-bibr">107</a>,<a href="#B108-cells-14-00013" class="html-bibr">108</a>,<a href="#B109-cells-14-00013" class="html-bibr">109</a>,<a href="#B110-cells-14-00013" class="html-bibr">110</a>,<a href="#B111-cells-14-00013" class="html-bibr">111</a>,<a href="#B112-cells-14-00013" class="html-bibr">112</a>,<a href="#B113-cells-14-00013" class="html-bibr">113</a>,<a href="#B114-cells-14-00013" class="html-bibr">114</a>,<a href="#B115-cells-14-00013" class="html-bibr">115</a>,<a href="#B117-cells-14-00013" class="html-bibr">117</a>,<a href="#B121-cells-14-00013" class="html-bibr">121</a>,<a href="#B126-cells-14-00013" class="html-bibr">126</a>,<a href="#B127-cells-14-00013" class="html-bibr">127</a>]. LATS1/2, MST 1/2, and YAP/TAZ regulate the expression of several interleukins and chemokines, which are SASP factors, via the transcription factors C/EBPβ and NF-κB. Hippo pathway-associated factors contribute to cellular senescence by regulating the expression of SASP factors through a number of molecules. Arrows and vertical bars indicate potentiating and inhibitory effects. Dashed lines indicate potential.</p>
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<p>Relationship between the Hippo pathway and aging-related diseases [<a href="#B57-cells-14-00013" class="html-bibr">57</a>,<a href="#B120-cells-14-00013" class="html-bibr">120</a>,<a href="#B135-cells-14-00013" class="html-bibr">135</a>,<a href="#B136-cells-14-00013" class="html-bibr">136</a>,<a href="#B140-cells-14-00013" class="html-bibr">140</a>,<a href="#B146-cells-14-00013" class="html-bibr">146</a>,<a href="#B147-cells-14-00013" class="html-bibr">147</a>,<a href="#B148-cells-14-00013" class="html-bibr">148</a>,<a href="#B150-cells-14-00013" class="html-bibr">150</a>]. The Hippo pathway is involved in physical aging by regulating cellular senescence in tissues. Arrows indicate potentiation and dashed lines indicate potential.</p>
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23 pages, 1440 KiB  
Review
Direct Vascular Effects of Angiotensin II (A Systematic Short Review)
by György L. Nádasy, András Balla, Gabriella Dörnyei, László Hunyady and Mária Szekeres
Int. J. Mol. Sci. 2025, 26(1), 113; https://doi.org/10.3390/ijms26010113 (registering DOI) - 26 Dec 2024
Abstract
The octapeptide angiotensin II (Ang II) is a circulating hormone as well as a locally formed agonist synthesized by the angiotensin-converting enzyme (ACE) of endothelial cells. It forms a powerful mechanism to control the amount and pressure of body fluids. All main effects [...] Read more.
The octapeptide angiotensin II (Ang II) is a circulating hormone as well as a locally formed agonist synthesized by the angiotensin-converting enzyme (ACE) of endothelial cells. It forms a powerful mechanism to control the amount and pressure of body fluids. All main effects are directed to save body salt and water and ensure blood pressure under basic conditions and in emergencies. All blood vessels respond to stimulation by Ang II; the immediate response is smooth muscle contraction, increasing vascular resistance, and elevating blood pressure. Such effects are conveyed by type 1 angiotensin receptors (AT1Rs) located in the plasma membrane of both endothelial and vascular smooth muscle cells. AT1Rs are heterotrimeric G protein-coupled receptors (GPCRs), but their signal pathways are much more complicated than other GPCRs. In addition to Gq/11, the G12/13, JAK/STAT, Jnk, MAPK, and ERK 1/2, and arrestin-dependent and -independent pathways are activated because of the promiscuous attachment of different signal proteins to the intracellular G protein binding site and to the intracellular C terminal loop. Substantial changes in protein expression follow, including the intracellular inflammation signal protein NF-κB, endothelial contact proteins, cytokines, matrix metalloproteinases (MMPs), and type I protocollagen, eliciting the inflammatory transformation of endothelial and vascular smooth muscle cells and fibrosis. Ang II is an important contributor to vascular pathologies in hypertensive, atherosclerotic, and aneurysmal vascular wall remodeling. Such direct vascular effects are reviewed. In addition to reducing blood pressure, AT1R antagonists and ACE inhibitors have a beneficial effect on the vascular wall by inhibiting pathological wall remodeling. Full article
(This article belongs to the Special Issue Renin-Angiotensin System in Health and Diseases)
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<p>Signal pathways of the angiotensin type 1 receptor (AT<sub>1</sub>R) in vascular cells. (<b>a</b>). Dimerization of the receptor molecule might cause mutual inhibition. (<b>b</b>). The “classical” heterotrimeric G protein activation pathway (with G<sub>αq/11</sub>) induces smooth muscle contraction. Increased intracellular Ca<sup>2+</sup> and membrane DAG activate PKC enzyme subtypes with diverse effects. (<b>c</b>). “Promiscuous” association of the intracellular G protein binding site with other heterotrimeric G proteins, altered specificity is supposed to be controlled by different RGS proteins. (<b>d</b>). Receptor internalization, digestion, or recycling to the membrane after β-arrestin binding. threonin (T) and serine (S) phosphorylations by GRK kinases at the intracellular C terminal loop promote β-arrestin binding. The binding of heterotrimeric G proteins to their binding site will be prevented. (<b>e</b>). Diverse intracellular signal pathways are activated by C terminal phosphorylations and β-arresting binding. Abbreviations: Ang II, angiotensin II; AT<sub>1</sub>R, angiotensin type 1 receptor molecule; N, N terminal; C, C terminal; PLC, phospholipase C; IP<sub>3</sub>, inositol triphosphate; CaM, calmodulin; MLCK, myosin light chain kinase; G<sub>q/11</sub>, G<sub>12/13</sub>, G<sub>i/o</sub>, heterotrimeric G proteins with corresponding α subunits; RGS, regulator of G protein signaling; NO, nitrogen oxide; PG, prostaglandins; RhoA, small GTPase; ROCK, Rho-associated protein kinase; Arr, β-Arrestin; GRK, G protein-coupled receptor kinase; Ras, Raf, MEK, components in the MAP (mitogen-activated protein) kinase cascade; ERK-P, extracellular signal-regulated kinase, phosphorylated (activated) form; JAK/STAT, cytokine signal pathway; NADPH oxidase, main source of reactive oxygen species (ROS) in mammalian tissues; JNK, apoptotic signal protein; ADAM, membrane metalloproteinase, it cleaves off membrane-bound EGFR ligand; EGF, released peptide with EGF (epithelial growth factor) activity; EGFR, epithelial growth factor receptor. Blue color marks signal pathways through the G protein binding site, green color marks signal pathways through the C terminal loop.</p>
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<p>Ang II-induced pathologic remodeling of the vascular wall. (<b>a</b>). Remodeling of the endothelium and of the media (<b>b</b>). Role of Ang II in atherosclerotic vessel wall remodeling. Abbreviations: Ang I, angiotensin I; Ang II, Angiotensin II; ACE, angiotensin-converting enzyme; MMP, matrix metalloproteinase; TGFbeta, transforming growth factor beta; ROS, reactive oxygen species.</p>
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<p>A schematic, concise description of direct angiotensin II effects on the vascular wall. Abbreviations: Ang II, angiotensin II; ACE, angiotensin-converting enzyme; AT<sub>1</sub>R, angiotensin type 1 receptor; GPCR, G protein-coupled receptor; G<sub>α</sub>, α subunit of heterotrimeric G protein; PLC, phospholipase C, IP3, inositol triphosphate; MLCK, myosin light chain kinase; VSMC, vascular smooth muscle cell; NO, nitric oxide; Rho, small GTPase; ROCK, Rho-associated kinase; MLCP, myosin light chain phosphatase; GRB, growth receptor binding protein; MAPK, mitogen-activated protein kinase; ERK1/2, extracellular signal-regulated kinases; Src, nonreceptor tyrosine kinase; JAK, Janus kinase; STAT, signal transducer and activator of transcription; JNK, c-Jun NH<sub>2</sub>-terminal kinase; NADPH, nicotinamide adenine dinucleotide phosphate, oxidoreductase coenzyme; ROS, reactive oxygen species; TGFß, transforming growth factor type β; EGF, epithelial growth factor; MMP, matrix metalloproteinase.</p>
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17 pages, 744 KiB  
Review
Mechanisms and Emerging Regulators of Neuroinflammation: Exploring New Therapeutic Strategies for Neurological Disorders
by Mi Eun Kim and Jun Sik Lee
Curr. Issues Mol. Biol. 2025, 47(1), 8; https://doi.org/10.3390/cimb47010008 (registering DOI) - 26 Dec 2024
Abstract
Neuroinflammation is a complex and dynamic response of the central nervous system (CNS) to injury, infection, and disease. While acute neuroinflammation plays a protective role by facilitating pathogen clearance and tissue repair, chronic and dysregulated inflammation contributes significantly to the progression of neurodegenerative [...] Read more.
Neuroinflammation is a complex and dynamic response of the central nervous system (CNS) to injury, infection, and disease. While acute neuroinflammation plays a protective role by facilitating pathogen clearance and tissue repair, chronic and dysregulated inflammation contributes significantly to the progression of neurodegenerative disorders such as Alzheimer’s disease, Parkinson’s disease, and Multiple Sclerosis. This review explores the cellular and molecular mechanisms underlying neuroinflammation, focusing on the roles of microglia, astrocytes, and peripheral immune cells. Key signaling pathways, including NF-κB, JAK-STAT, and the NLRP3 inflammasome, are discussed alongside emerging regulators such as non-coding RNAs, epigenetic modifications, and the gut–brain axis. The therapeutic landscape is evolving, with traditional anti-inflammatory drugs like NSAIDs and corticosteroids offering limited efficacy in chronic conditions. Immunomodulators, gene and RNA-based therapeutics, and stem cell methods have all shown promise for more specific and effective interventions. Additionally, the modulation of metabolic states and gut microbiota has emerged as a novel strategy to regulate neuroinflammation. Despite significant progress, challenges remain in translating these findings into clinically viable therapies. Future studies should concentrate on integrated, interdisciplinary methods to reduce chronic neuroinflammation and slowing the progression of neurodegenerative disorders, providing opportunities for revolutionary advances in CNS therapies. Full article
(This article belongs to the Special Issue The Role of Neuroinflammation in Neurodegenerative Diseases)
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<p>The major molecular pathways driving neuroinflammation in Alzheimer’s disease, highlighting their interconnected roles in perpetuating chronic inflammation. At the center of the diagram is neuroinflammation, which is fueled by four key pathways. The NF-κB pathway, activated by amyloid beta (Aβ) and tau proteins, promotes the production of pro-inflammatory cytokines such as TNF-α and IL-6, amplifying the inflammatory response. The NLRP3 inflammasome, triggered by Aβ, reactive oxygen species (ROS), and mitochondrial dysfunction, leads to the release of IL-1β and IL-18, further escalating neuroinflammation. The JAK-STAT pathway, induced by cytokines like IL-6, drives the activation of neurotoxic astrocytes, which contribute to neuronal damage. Finally, the MAPK pathway, stimulated by Aβ, tau, and oxidative stress, enhances ROS production and cytokine release, exacerbating oxidative damage and inflammation. Together, these pathways form a complex network that underpins the inflammatory processes observed in Alzheimer’s disease.</p>
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28 pages, 27768 KiB  
Article
Nootkatone Derivative Nootkatone-(E)-2-iodobenzoyl hydrazone Promotes Megakaryocytic Differentiation in Erythroleukemia by Targeting JAK2 and Enhancing JAK2/STAT3 and PKCδ/MAPK Crosstalk
by Yang Pan, Feng Xiao, Chaolan Pan, Hui Song, Peng Zhao, Meijun Chen, Liejun Huang, Jue Yang and Xiaojiang Hao
Cells 2025, 14(1), 10; https://doi.org/10.3390/cells14010010 (registering DOI) - 26 Dec 2024
Abstract
Erythroleukemia, a complex myeloproliferative disorder presenting as acute or chronic, is characterized by aberrant proliferation and differentiation of erythroid cells. Although nootkatone, a sesquiterpene derived from grapefruit peel and Alaska yellow cedar, has shown anticancer activity predominantly in solid tumors, its effects in [...] Read more.
Erythroleukemia, a complex myeloproliferative disorder presenting as acute or chronic, is characterized by aberrant proliferation and differentiation of erythroid cells. Although nootkatone, a sesquiterpene derived from grapefruit peel and Alaska yellow cedar, has shown anticancer activity predominantly in solid tumors, its effects in erythroleukemia remain unexplored. This study aimed to investigate the impact of nootkatone and its derivatives on erythroleukemia. Our results demonstrate that the nootkatone derivative nootkatone-(E)-2-iodobenzoyl hydrazone (N2) significantly inhibited erythroleukemia cell proliferation in a concentration- and time-dependent manner. More importantly, N2 induced megakaryocytic differentiation, as evidenced by significant morphological changes, and upregulation of megakaryocytic markers CD41 and CD61. In vivo, N2 treatment led to a marked increase in platelet counts and megakaryocytic cell counts. Mechanistically, N2 activated a crosstalk between the JAK2/STAT3 and PKCδ/MAPK signaling pathways, enhancing transcriptional regulation of key factors like GATA1 and FOS. Network pharmacology and experimental validation confirmed that N2 targeted JAK2, and knockdown of JAK2 abolished N2-induced megakaryocytic differentiation, underscoring JAK2’s critical role in erythroleukemia differentiation. In conclusion, N2 shows great promise as a differentiation therapy for erythroleukemia, offering a novel approach by targeting JAK2-mediated signaling pathways to induce megakaryocytic differentiation. Full article
(This article belongs to the Section Cell Signaling)
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<p>Nootkatone derivative N2 inhibits cell proliferation in erythroleukemia HEL and K562 cells. (<b>A</b>) Chemical structure of nootkatone derivative N2. (<b>B</b>) Scatter diagram presentation of the influence of nootkatone and its derivatives (20 μM) on cell viability of HEL and K562 cells for 72 h. The inhibition rate was measured by MTT assays, with the 0.1% DMSO group serving as the negative control. Inhibition rate = (negative control group—treatment group)/negative control group × 100%. (<b>C</b>,<b>D</b>) HEL and K562 cells were treated with varying concentrations of the nootkatone derivative N2 for 72 h, and cell viability was evaluated using MTT assays. (<b>E</b>,<b>F</b>) The influence of N2 on the proliferation of HEL and K562 cells was quantified through MTT assays. (<b>G</b>,<b>H</b>) Effects of N2 on morphological changes in HEL and K562 cells. Magnification: ×200. Scale bar: 100 µm. Data represented the mean ± SD of three independent experiments. * <span class="html-italic">p</span> &lt; 0.05, ** <span class="html-italic">p</span> &lt; 0.01, *** <span class="html-italic">p</span> &lt; 0.001 vs. the DMSO group.</p>
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<p>Nootkatone derivative N2 enhances multinucleation and CD41a expression in HEL and K562 cells. (<b>A</b>,<b>B</b>) Morphological analysis of HEL (<b>A</b>) and K562 (<b>B</b>) cells following treatment with varying concentrations of N2 for 72–96 h. Cells were subjected to Wright–Giemsa staining for morphological assessment. Magnification: ×400. Scale bar: 50 µm. (<b>C</b>,<b>D</b>) Immunofluorescence analysis was conducted on HEL (<b>C</b>) and K562 (<b>D</b>) cells treated with either DMSO or N2 for 72 h, revealing CD41a expression (green). Nuclear staining was performed using DAPI (blue). Magnification: ×400. Scale bar: 50 µm.</p>
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<p>Nootkatone derivative N2 increases the expression of megakaryocyte-specific markers in HEL cells. (<b>A,B</b>) Expression of CD41a and CD61 megakaryocyte-specific markers analyzed using flow cytometry in HEL cells. (<b>C</b>,<b>D</b>) Quantification of the percentage of CD41a<sup>+</sup> cells and CD61<sup>+</sup> cells in HEL cells. Data represent the mean ± SD of three independent experiments. ** <span class="html-italic">p</span> &lt; 0.01, *** <span class="html-italic">p</span> &lt; 0.001 vs. the DMSO group.</p>
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<p>Nootkatone derivative N2 increases the expression of megakaryocyte-specific markers in K562 cells. (<b>A</b>,<b>B</b>) Expression of CD41a and CD61 megakaryocyte-specific markers analyzed using flow cytometry in K562 cells. (<b>C</b>,<b>D</b>) Quantification of the percentage of CD41a<sup>+</sup> cells and CD61<sup>+</sup> cells in K562 cells. Data represent the mean ± SD of three independent experiments. *** <span class="html-italic">p</span> &lt; 0.001 vs. the DMSO group.</p>
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<p>Effect of nootkatone derivative N2 on cell cycle distribution in HEL and K562 cells. (<b>A</b>–<b>F</b>) HEL (<b>A</b>) and K562 (<b>D</b>) cells were exposed to indicated concentrations of N2 for either 72 h or 96 h. The cells were stained with PI and the percentage of cell cycle distribution was analyzed by flow cytometry. The proportions of cell cycle distribution at G1, S, and G2 phases in HEL (<b>B</b>,<b>C</b>) and K562 (<b>E</b>,<b>F</b>) cells at various time points. Data are expressed as the mean ± SD, with each experiment conducted in triplicate. *** <span class="html-italic">p</span> &lt; 0.001 vs. the DMSO group.</p>
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<p>N2 treatment was associated with an increase in polyploidy in HEL and K562 cells. (<b>A</b>–<b>D</b>) Polyploid cells in N2-treated HEL (<b>A</b>) and K562 (<b>C</b>) cells were analyzed by flow cytometry. The proportion of polyploid cells in HEL (<b>B</b>) and K562 (<b>D</b>) cells. Data are expressed as the mean ± SD. Each experiment was repeated in triplicate. * <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 vs. the DMSO group.</p>
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<p>Nootkatone derivative N2 activates the PKCδ/MAPK signaling pathway and its downstream megakaryocytic differentiation-related transcription factors. (<b>A</b>–<b>D</b>) Upon treating with N2 (2, 4, 8 μM), the expression levels of p-PKCδ, PKCδ, p-MEK, MEK, p-ERK, ERK, and GATA1 detected using Western blotting in HEL (<b>A</b>) and K562 (<b>C</b>) cells. Densitometry analysis of these proteins in HEL (<b>B</b>) and K562 (<b>D</b>) cells. (<b>E</b>,<b>F</b>) Effects of N2 on the mRNA expression levels of seven transcription factors relevant to megakaryocytic differentiation in HEL (<b>E</b>) and K562 (<b>F</b>) cells. All data are expressed as the mean ± SD. GAPDH was used as loading control. Each experiment was repeated in triplicate. * <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 vs. the DMSO group.</p>
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<p>Nootkatone derivative N2 activates the JAK2/STAT3 signaling pathway in HEL and K562 cells. (<b>A</b>) JAK2 was identified as a potential target based on the intersection of N2-predicted targets with established targets associated with acute myeloid leukemia. (<b>B</b>–<b>E</b>) HEL (<b>B</b>) and K562 (<b>C</b>) cells were treated with N2 at the indicated doses. The expression levels of p-JAK2, JAK2, p-STAT3, and STAT3 were analyzed by Western blotting. Densitometry analysis of p-JAK2, JAK2, p-STAT3, and STAT3 in HEL (<b>D</b>) and K562 (<b>E</b>) cells. All data are expressed as the mean ± SD, with GAPDH serving as the loading control. Each experiment was repeated in triplicate. ** <span class="html-italic">p</span> &lt; 0.01, *** <span class="html-italic">p</span> &lt; 0.001 vs. the DMSO group.</p>
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<p>Nootkatone derivative N2 promotes megakaryocytic differentiation via activation of the JAK2/STAT3 signaling pathways. (<b>A</b>,<b>B</b>) JAK2/STAT3 pathway specific inhibitor WP1066 treatment inhibited N2-induced increases in cell size, multinucleation in HEL and K562 cells via Wright–Giemsa staining. Magnification: ×400. Scale bar: 50 µm. (<b>C</b>,<b>D</b>) HEL and K562 cells were treated with N2 (8 μM) either alone or in combination with JAK2/STAT3 inhibitor, WP1066 (1 μM), and the expression levels of CD41a and CD61 analyzed using flow cytometry. (<b>E</b>–<b>H</b>) Quantification of the percentage of CD41a<sup>+</sup> cells and CD61<sup>+</sup> cells in HEL (<b>E</b>,<b>F</b>) and K562 (<b>G</b>,<b>H</b>) cells. Data are expressed as the mean ± SD. Each experiment was repeated in triplicate. ** <span class="html-italic">p</span> &lt; 0.01, *** <span class="html-italic">p</span> &lt; 0.001 vs. the DMSO group. <sup>##</sup> <span class="html-italic">p</span> &lt; 0.01, <sup>###</sup> <span class="html-italic">p</span> &lt; 0.001 vs. N2 group.</p>
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<p>Nootkatone derivative N2 promotes megakaryocytic differentiation via activation of the PKCδ/MAPK signaling pathways. (<b>A</b>,<b>B</b>) Treatment of HEL and K562 cells with N2 at a concentration of 8 μM, both independently and in conjunction with the PKCδ-specific inhibitor Rottlerin (1 μM). The cells were subjected to Wright–Giemsa staining for morphological assessment. Magnification: ×400. Scale bar: 50 µm. (<b>C</b>,<b>D</b>) HEL and K562 cells were treated with N2 (8 μM) in the absence or presence of Rottlerin (1 μM), and expression of CD41a and CD61 analyzed using flow cytometry. (<b>E</b>–<b>H</b>) Quantification of the percentage of CD41a<sup>+</sup> cells and CD61<sup>+</sup> cells in HEL (<b>E</b>,<b>F</b>) and K562 (<b>G</b>,<b>H</b>) cells. Data are presented as the mean ± SD. Each experiment was repeated in triplicate. *** <span class="html-italic">p</span> &lt; 0.001 vs. the DMSO group. <sup>#</sup> <span class="html-italic">p</span> &lt; 0.05, <sup>###</sup> <span class="html-italic">p</span> &lt; 0.001 vs. N2 group.</p>
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<p>WP1066 treatment significantly reduced N2-induced phosphorylation of JAK2, STAT3, PKCδ, MEK, and ERK, as well as the expression of GATA1. (<b>A</b>,<b>B</b>) HEL and K562 cells were treated with N2 (8 μM) and/or WP1066 (1 μM), and the protein expression levels of p-JAK2, JAK2, p-STAT3, STAT3, p-PKCδ, PKCδ, p-MEK, MEK, p-ERK, ERK, and GATA1 were detected using Western blotting. (<b>C</b>,<b>D</b>) Densitometry analysis of these proteins in HEL (<b>C</b>) and K562 (<b>D</b>) cells. Data are presented as the mean ± SD. GAPDH was used as loading control. Each experiment was repeated in triplicate. *** <span class="html-italic">p</span> &lt; 0.001 vs. the DMSO group. <sup>#</sup> <span class="html-italic">p</span> &lt; 0.05, <sup>##</sup> <span class="html-italic">p</span> &lt; 0.01, <sup>###</sup> <span class="html-italic">p</span> &lt; 0.001 vs. N2 group.</p>
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<p>Rottlerin significantly diminished N2-induced PKCδ, STAT3, MEK and ERK phosphorylation. (<b>A</b>,<b>B</b>) HEL and K562 cells were treated with N2 (8 μM) in the absence or presence of Rottlerin (1 μM), and the proteins expression of p-JAK2, JAK2, p-STAT3, STAT3, p-PKCδ, PKCδ, p-MEK, MEK, p-ERK, ERK and GATA1 were detected using Western blotting. (<b>C</b>,<b>D</b>) Densitometry analysis of these proteins in HEL (<b>C</b>) and K562 (<b>D</b>) cells. Data are presented as the mean ± SD. GAPDH was used as loading control. Each experiment was repeated in triplicate. * <span class="html-italic">p</span> &lt; 0.05, *** <span class="html-italic">p</span> &lt; 0.001 vs. the DMSO group. <sup>###</sup> <span class="html-italic">p</span> &lt; 0.001 vs. N2 group.</p>
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<p>Nootkatone derivative N2 binds to JAK2. (<b>A</b>) Molecular docking of N2 and JAK2 was conducted using AutoDock Vina 1.1.2. (<b>B</b>) CETSA was performed to assess the binding interactions between N2 and JAK2. (<b>C</b>) The stability of the JAK2 protein across varying temperatures was quantified using Western blotting analysis. (<b>D</b>) The DARTS experiments confirmed the binding of N2 to the JAK2 protein. (<b>E</b>) Densitometry analysis of JAK2. Data are presented as the mean ± SD. Each experiment was repeated in triplicate. <sup>###</sup> <span class="html-italic">p</span> &lt; 0.001 vs. lysates group, *** <span class="html-italic">p</span> &lt; 0.001 vs. pronase alone group.</p>
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<p>Nootkatone derivative N2-mediated megakaryocytic differentiation in erythroleukemia cells is JAK2-dependent. (<b>A</b>) Morphological analysis was conducted using Wright–Giemsa staining on LV-NC and LV-sh-JAK2 HEL cells exposed to 8 μM N2. Magnification: ×400. Scale bar: 50 µm. (<b>B</b>) Flow cytometry was employed to assess the expression levels of CD41a and CD61 in LV-NC and LV-sh-JAK2 HEL cells treated with 8 μM N2. (<b>C</b>,<b>D</b>) Quantification of the percentage of CD41a<sup>+</sup> and CD61<sup>+</sup> cells. (<b>E</b>) The expression of p-JAK2, JAK2, p-PKCδ, PKCδ, p-STAT3, STAT3, p-MEK, and MEK in LV-NC and LV-sh-JAK2 HEL cells treated with 8 μM N2 were measured by Western blotting. (<b>F</b>) Densitometry analysis of these proteins. All data are presented as the mean ± SD. Each experiment was repeated in triplicate. ** <span class="html-italic">p</span> &lt; 0.01, *** <span class="html-italic">p</span> &lt; 0.001 vs. LV-NC/DMSO group. <sup>###</sup> <span class="html-italic">p</span> &lt; 0.001 vs. LV-NC/N2-8 µM group.</p>
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<p>Nootkatone derivative N2 accelerates megakaryocytic differentiation and suppresses erythroleukemia in vivo. (<b>A</b>) Spleen size of mice in different experimental groups. (<b>B</b>) Spleen weight presented as mean ± SD (<span class="html-italic">n</span> = 5). (<b>C</b>) Hematocrit values. (<b>D</b>) Platelet counts. (<b>E</b>) Flow cytometric analysis of CD41 and CD61 expression of spleen of each groups. (<b>F</b>,<b>G</b>) The histogram represents the percentage of CD41<sup>+</sup> and CD61<sup>+</sup> cells of spleen in each groups. (<b>H</b>) Representative H&amp;E stained images of spleen from each groups. The yellow arrow represents megakaryocytes. Magnification: ×400. Scale bar: 50 µm. Data represent the mean ± SD (<span class="html-italic">n</span> = 3). * <span class="html-italic">p</span> &lt; 0.05, ** <span class="html-italic">p</span> &lt; 0.01, *** <span class="html-italic">p</span> &lt; 0.001 vs. model group. <sup>#</sup> <span class="html-italic">p</span> &lt; 0.05, <sup>##</sup> <span class="html-italic">p</span> &lt; 0.01, <sup>###</sup> <span class="html-italic">p</span> &lt; 0.001 vs. normal group.</p>
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<p>Nootkatone derivative N2 activates JAK2/STAT3 and PKCδ/MAPK signaling pathways. (<b>A</b>) The expression of p-JAK2, JAK2, p-PKCδ, PKCδ, p-STAT3, STAT3, p-MEK, MEK, p-ERK, and ERK of spleen tissue from each groups were measured by Western blotting. (<b>B</b>) Densitometry analysis of these proteins. (<b>C</b>) The impact of N2 on the mRNA expression of nine transcription factors related to megakaryocytic differentiation in spleen tissue. Data are expressed as the mean ± SD (<span class="html-italic">n</span> = 3). * <span class="html-italic">p</span> &lt; 0.05, ** <span class="html-italic">p</span> &lt; 0.01, *** <span class="html-italic">p</span> &lt; 0.001 vs. model group. <sup>#</sup> <span class="html-italic">p</span> &lt; 0.05, <sup>##</sup> <span class="html-italic">p</span> &lt; 0.01, <sup>###</sup> <span class="html-italic">p</span> &lt; 0.001 vs. normal group.</p>
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<p>Illustration of the role and mechanism of nootkatone derivative N2 in promoting megakaryocytic differentiation in erythroleukemia. The red arrow indicates up-regulation.</p>
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50 pages, 1756 KiB  
Review
Engineered Cellular Therapies for the Treatment of Thoracic Cancers
by Spencer M. Erickson, Benjamin M. Manning, Akhilesh Kumar and Manish R. Patel
Cancers 2025, 17(1), 35; https://doi.org/10.3390/cancers17010035 (registering DOI) - 26 Dec 2024
Abstract
Thoracic malignancies (lung cancers and malignant pleural mesothelioma) are prevalent worldwide and are associated with high morbidity and mortality. Effective treatments are needed for patients with advanced disease. Cell therapies are a promising approach to the treatment of advanced cancers that make use [...] Read more.
Thoracic malignancies (lung cancers and malignant pleural mesothelioma) are prevalent worldwide and are associated with high morbidity and mortality. Effective treatments are needed for patients with advanced disease. Cell therapies are a promising approach to the treatment of advanced cancers that make use of immune effector cells that have the ability to mediate antitumor immune responses. In this review, we discuss the prospect of chimeric antigen receptor-T (CAR-T) cells, natural killer (NK) cells, T cell receptor-engineered (TCR-T) cells, and tumor-infiltrating lymphocytes (TILs) as treatments for thoracic malignancies. CAR-T cells and TILs have proven successful in several hematologic cancers and advanced melanoma, respectively, but outside of melanoma, results have thus far been unsuccessful in most other solid tumors. NK cells and TCR-T cells are additional cell therapy platforms with their own unique advantages and challenges. Obstacles that must be overcome to develop effective cell therapy for these malignancies include selecting an appropriate target antigen, combating immunosuppressive cells and signaling molecules present in the tumor microenvironment, persistence, and delivering a sufficient quantity of antitumor immune cells to the tumor. Induced pluripotent stem cells (iPSCs) offer great promise as a source for both NK and T cell-based therapies due to their unlimited expansion potential. Here, we review clinical trial data, as well as recent basic scientific advances that offer insight into how we may overcome these obstacles, and provide an overview of ongoing trials testing novel strategies to overcome these obstacles. Full article
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<p>Overview of the barriers faced by cell therapies in the treatment of thoracic cancers. Tumor and TME-intrinsic factors limiting the efficacy of cell therapies include selection of an appropriate antigen target, antigen escape, hypoxia, immunosuppressive cytokines and chemicals such as lactate and adenosine, low nutrient availability, lack of chemotactic signals to promote immune cell recruitment, immunosuppressive cells (Tregs, MDSCs, TAMs, etc.), and a dense desmoplastic matrix that prevents effective trafficking of immune cells to tumor cells. Limitations intrinsic to T and NK cell therapies include an insufficient quantity of cells delivered to the tumor, variation in the quality of cells selected for ex vivo expansion, inability to traffic through the TME to tumor cells, lack of persistence, development of an exhausted phenotype, requirement of exogenous cytokine support, the presence of immune checkpoints, the risk of GVHD, iCANS, and toxicity related to off-target, on-target, off-tumor, and cytokine release syndrome. These limitations intrinsic to the cell therapies are shared amongst each of the cell therapy types discussed. Created in BioRender. Erickson, S. <a href="https://BioRender.com/p99g888" target="_blank">https://BioRender.com/p99g888</a> (accessed on 16 December 2024).</p>
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<p>Strategies being explored to improve the efficacy of cell therapies in thoracic cancers. Cell source is an important consideration for cell therapy products. iPSCs allow for efficient expansion of multigene edited off-the-shelf T and NK cell therapies and are a promising avenue to explore in future clinical trials. Additional considerations that may optimize the efficacy of T and NK cell therapies include: repeat infusion strategies to overcome the issues of persistence and insufficient quantity of cells; optimizing conditioning regimens to effectively deplete Tregs; timing infusions according to circadian rhythms present in T cells and endothelial cells in the TME; dual antigen targeting to prevent antigen escape; combination with BiTEs, BiKEs, TriKEs, or mAbs to improve antitumor efficacy via improved targeting and improve safety by increasing specificity; combination with oncolytic viruses; combination with vaccines; targeting or preventing the shedding of MICA/B; sensitization with radiation conditioning; improving CAR-T cell trafficking with localized microwave ablation; targeting CAFs which produce the dense desmoplastic matrix of the TME; engineering cells to co-express chemokine receptors or ligands; inhibiting N-glycan synthesis with 2DG; blocking CSF-1R with antibodies, genetic deletion or inactivation of TGFβRII, and genetic deletion of A2AR; local delivery of CAR-T cells to bypass the issue of effective trafficking to target sites; utilizing T cells with an effector memory phenotype or stem-like properties; and utilizing NK cells with adaptive or memory-like properties. Created in BioRender. Erickson, S. (2024). <a href="https://BioRender.com/a73j495" target="_blank">https://BioRender.com/a73j495</a> (accessed on 29 October 2024).</p>
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29 pages, 2414 KiB  
Review
Current Status of Bioprinting Using Polymer Hydrogels for the Production of Vascular Grafts
by Jana Matějková, Denisa Kaňoková and Roman Matějka
Gels 2025, 11(1), 4; https://doi.org/10.3390/gels11010004 (registering DOI) - 26 Dec 2024
Abstract
Cardiovascular disease is one of the leading causes of death and serious illness in Europe and worldwide. Conventional treatment—replacing the damaged blood vessel with an autologous graft—is not always affordable for the patient, so alternative approaches are being sought. One such approach is [...] Read more.
Cardiovascular disease is one of the leading causes of death and serious illness in Europe and worldwide. Conventional treatment—replacing the damaged blood vessel with an autologous graft—is not always affordable for the patient, so alternative approaches are being sought. One such approach is patient-specific tissue bioprinting, which allows for precise distribution of cells, material, and biochemical signals. With further developmental support, a functional replacement tissue or vessel can be created. This review provides an overview of the current state of bioprinting for vascular graft manufacturing and summarizes the hydrogels used as bioinks, the material of carriers, and the current methods of fabrication used, especially for vessels smaller than 6 mm, which are the most challenging for cardiovascular replacements. The fabrication methods are divided into several sections—self-supporting grafts based on simple 3D bioprinting and bioprinting of bioinks on scaffolds made of decellularized or nanofibrous material. Full article
(This article belongs to the Special Issue Application of Hydrogels in 3D Bioprinting for Tissue Engineering)
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Graphical abstract

Graphical abstract
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<p>Vascular surgery techniques as an alternative for revascularization treatment. An illustration was created with <a href="https://www.biorender.com/" target="_blank">https://www.biorender.com/</a>, accessed on 12 November 2024. BioRender.com.</p>
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<p>The requirements for ideal vascular replacement are broad and cover many areas. An illustration was created with <a href="https://www.biorender.com/" target="_blank">https://www.biorender.com/</a>, accessed on 28 October 2024.</p>
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<p>Different methods of creating vascular grafts. Highlighted in blue are classical additive bioprinting techniques, which use hydrogel, cells, and other support materials to create a custom 3D construct. The yellow-colored are replacements created by a combination of bioprinting and acellular support of decellularized or electrospun fibers. The green-colored ones are methods that involve molding hydrogels or rolling sheets with cells into tubes. Due to the absence of bioprinting, these two techniques are not the focus of the paper. An illustration was created with <a href="https://www.biorender.com/" target="_blank">https://www.biorender.com/</a>, accessed on 10 October 2024.</p>
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<p>The process of bioprinting on decellularized grafts involves the following: harvesting tissues from donors or cadavers; removing cells while preserving the extracellular matrix; washing and sterilizing to eliminate debris and prevent immune responses; enhancing scaffolds with biomaterials and growth factors; preparing for techniques like cell seeding and modification; embedding in an in vivo environment to support cell attachment and growth. An illustration was created with <a href="https://www.biorender.com/" target="_blank">https://www.biorender.com/</a>, accessed on 15 October 2024.</p>
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18 pages, 13184 KiB  
Article
Lactate Promotes Hypoxic Granulosa Cells’ Autophagy by Activating the HIF-1α/BNIP3/Beclin-1 Signaling Axis
by Yitong Pan, Gang Wu, Min Chen, Xiumei Lu, Ming Shen, Hongmin Li and Honglin Liu
Genes 2025, 16(1), 14; https://doi.org/10.3390/genes16010014 - 26 Dec 2024
Abstract
Background/Objectives: The avascular nature of the follicle creates a hypoxic microenvironment, establishing a niche where granulosa cells (GCs) rely on glycolysis to produce energy in the form of lactate (L-lactate). Autophagy, an evolutionarily conserved stress-response process, involves the formation of autophagosomes to encapsulate [...] Read more.
Background/Objectives: The avascular nature of the follicle creates a hypoxic microenvironment, establishing a niche where granulosa cells (GCs) rely on glycolysis to produce energy in the form of lactate (L-lactate). Autophagy, an evolutionarily conserved stress-response process, involves the formation of autophagosomes to encapsulate intracellular components, delivering them to lysosomes for degradation. This process plays a critical role in maintaining optimal follicular development. However, whether hypoxia regulates autophagy in GCs via lactate remains unclear. Methods: In this study, we investigated lactate-induced autophagy under hypoxia by utilizing glycolysis inhibitors or silencing related genes. Results: We observed a significant increase in autophagy in ovarian GCs under hypoxic conditions, indicated by elevated LC3II levels and reduced P62 levels. Suppressing lactate production through glycolytic inhibitors (2-DG and oxamate) or silencing lactate dehydrogenase (LDHA/LDHB) effectively reduced hypoxia-induced autophagy. Further investigation revealed that the HIF1-α/BNIP3/Beclin-1 axis is essential for lactate-induced autophagy under hypoxic conditions. Inhibiting HIF-1α activity using siRNAs or PX-478 downregulated BNIP3 expression and subsequently suppressed autophagy. Similarly, BNIP3 silencing with siRNAs repressed lactate-induced autophagy in hypoxic conditions. Mechanistically, immunoprecipitation experiments showed that BNIP3 disrupted pre-existing Bcl-2/Beclin-1 complexes by competing with Bcl-2 to form Bcl-2/BNIP3 complexes. This interaction released Beclin-1, which subsequently triggered lactate-induced autophagy under hypoxic conditions. Conclusions: These findings unveil a novel mechanism by which hypoxia regulates GC autophagy through lactate production, highlighting its potential role in sustaining follicular development under hypoxic conditions. Full article
(This article belongs to the Special Issue Gene Regulation of Development and Evolution in Mammals)
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<p>Hypoxia promotes autophagy of ovarian GCs through stimulation of lactate production. (<b>A</b>) GCs were treated with 15 mM 2-DG or 15 mM oxamate for 2 h, followed by 12 h of hypoxia, and protein levels of LC3 and p62 were determined by Western blot. (<b>B</b>) Quantitative analysis showed a significant increase in LC3-I to LC3-II conversion and (<b>C</b>) a decrease in p62 levels, with data presented as the mean ± SD (<span class="html-italic">n</span> ≥ 3, **** <span class="html-italic">p</span> &lt; 0.0001; *** <span class="html-italic">p</span> &lt; 0.001). (<b>D</b>) GFP-LC3 plasmid transfection revealed increased puncta under hypoxia, visualized by confocal microscopy, and (<b>E</b>) the number of GFP-LC3 puncta per cell was significantly elevated, with data from at least 5 cells per group (*** <span class="html-italic">p</span> &lt; 0.001; ** <span class="html-italic">p</span> &lt; 0.01; ns, not significant). (<b>F</b>) Cells treated with 15 mM 2-DG or oxamate, with or without 15 mM Nala supplementation after 2 h, and cultured under hypoxia or normoxia for 12 h showed altered LC3 and p62 levels by Western blot. (<b>G</b>) Quantification indicated a significant effect of Nala on LC3-I to LC3-II conversion and (<b>H</b>) p62 reduction (<span class="html-italic">n</span> ≥ 3, **** <span class="html-italic">p</span> &lt; 0.0001; * <span class="html-italic">p</span> &lt; 0.05). (<b>I</b>) Immunofluorescence confirmed GFP-LC3 punctum localization, and (<b>J</b>) punctum quantification showed consistent results. At least 5 cells were counted per group (**** <span class="html-italic">p</span> &lt; 0.0001; *** <span class="html-italic">p</span> &lt; 0.001). (<b>K</b>) Cells treated with 15 mM oxamate and 50 μM CQ, with or without 15 mM Nala after 2 h, under hypoxia for 12 h displayed significant changes in LC3 and p62 levels by Western blot, with quantitative analysis showing effects on (<b>L</b>) LC3-I to LC3-II conversion and (<b>M</b>) p62 levels (n ≥ 3,**** <span class="html-italic">p</span> &lt; 0.0001; *** <span class="html-italic">p</span> &lt; 0.001; ** <span class="html-italic">p</span> &lt; 0.01; * <span class="html-italic">p</span> &lt; 0.05). Error bars represent the standard deviation of the mean.</p>
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<p>Lactate actively induces autophagy in GCs. (<b>A</b>) Cells were cultured under normoxia for 12 h with or without the addition of 15 mM Nala. Intracellular LC3 and p62 protein levels were detected by Western blot. (<b>B</b>) Quantitative analysis of LC3-I to LC3-II conversion and (<b>C</b>) decreases in p62 levels, with data presented as the mean ± SD; <span class="html-italic">n</span> ≥ 3; **** <span class="html-italic">p</span> &lt; 0.0001; ** <span class="html-italic">p</span> &lt; 0.01. (<b>D</b>) Immunofluorescence localization of GFP-LC3 in granulosa cells. (<b>E</b>) The number of GFP-LC3 puncta per cell was quantified. At least 5 cells were counted per group, and data are presented as the mean ± SD; * <span class="html-italic">p</span> &lt; 0.05. (<b>F</b>) Protein levels of LC3 and p62 were assessed after inhibition of lactate with 3 mM α-CHCA, with or without the addition of 15 mM Nala, and quantified. (<b>G</b>) Quantitative analysis of LC3-I to LC3-II conversion. Data are presented as the mean ± SD; <span class="html-italic">n</span> ≥ 3; *** <span class="html-italic">p</span> &lt; 0.001; * <span class="html-italic">p</span> &lt; 0.05. (<b>H</b>) Quantitative analysis of p62 protein levels. Data are presented as the mean ± SD; ** <span class="html-italic">p</span> &lt; 0.01. (<b>I</b>) Immunofluorescence localization of GFP-LC3 in granulosa cells. (<b>J</b>) The number of GFP-LC3 puncta per cell was quantified. Data are presented as the mean ± SD; * <span class="html-italic">p</span> &lt; 0.05. At least 5 cells were counted per group. (<b>K</b>) After 50 μM CQ treatment for 2 h, cells were cultured under normoxia with or without 15 mM Nala. Protein levels of LC3 and p62 were detected and quantified. (<b>L</b>) Quantitative analysis of LC3-I to LC3-II conversion. Data are presented as the mean ± SD; <span class="html-italic">n</span> ≥ 3; *** <span class="html-italic">p</span> &lt; 0.001; ** <span class="html-italic">p</span> &lt; 0.01. (<b>M</b>) Quantitative analysis of p62 protein levels. Data are presented as the mean ± SD; <span class="html-italic">n</span> ≥ 3; **** <span class="html-italic">p</span> &lt; 0.0001; * <span class="html-italic">p</span> &lt; 0.05. Error bars represent the standard deviation of the mean.</p>
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<p>Lactate promotes activation of the HIF-1α/BNIP3/Beclin-1 pathway. (<b>A</b>) GCs were treated with 15 mM 2-DG or 15 mM oxamate and exposed to hypoxia or normoxia for 12 h. Protein levels of HIF-1α and BNIP3 were detected by Western blot and quantified. (<b>B</b>) Quantitative analysis of HIF-1α and BNIP3 protein levels. Data represent the mean ± SD; <span class="html-italic">n</span> ≥ 3; **** <span class="html-italic">p</span> &lt; 0.0001; * <span class="html-italic">p</span> &lt; 0.05. (<b>C</b>) Cells were transfected with or without siRNAs targeting <span class="html-italic">LDHA</span> and <span class="html-italic">LDHB</span> for 12 h and then exposed to different oxygen conditions. Protein levels of HIF-1α and BNIP3 were detected and quantified. (<b>D</b>) Quantitative analysis of HIF-1α and BNIP3 protein levels. Data represent the mean ± SD; <span class="html-italic">n</span> ≥ 3; ** <span class="html-italic">p</span> &lt; 0.01; * <span class="html-italic">p</span> &lt; 0.05. (<b>E</b>) GCs were treated with 15 mM 2-DG or 15 mM oxamate for 2 h with or without 15 mM Nala and then cultured under hypoxia or normoxia for 12 h. Protein levels of HIF-1α and BNIP3 were detected and quantified. (<b>F</b>) Quantitative analysis of HIF-1α and BNIP3 protein levels. Data represent the mean ± SD; <span class="html-italic">n</span> ≥ 3; **** <span class="html-italic">p</span> &lt; 0.0001; ** <span class="html-italic">p</span> &lt; 0.01. (<b>G</b>) After silencing LDHA and LDHB, with or without the addition of 15 mM Nala, cells were cultured under hypoxia. Protein levels of HIF-1α and BNIP3 were detected and quantified. (<b>H</b>) Quantitative analysis of HIF-1α and BNIP3 protein levels. Data represent the mean ± SD; <span class="html-italic">n</span> ≥ 3; **** <span class="html-italic">p</span> &lt; 0.0001; *** <span class="html-italic">p</span> &lt; 0.001; ** <span class="html-italic">p</span> &lt; 0.01. (<b>I</b>) Cells were treated with 3 mM α-CHCA for 2 h to inhibit lactate uptake, followed by the addition of 15 mM Nala, and cultured under hypoxia. Protein levels of HIF-1α and BNIP3 were detected and quantified. (<b>J</b>) Densitometric analysis of HIF-1α and BNIP3 protein levels. Data represent the mean ± SD; <span class="html-italic">n</span> ≥ 3; **** <span class="html-italic">p</span> &lt; 0.0001; *** <span class="html-italic">p</span> &lt; 0.001; * <span class="html-italic">p</span> &lt; 0.05. Error bars represent the standard deviation of the mean.</p>
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<p>HIF-1α enhances lactate-driven autophagy in GCs under hypoxia. (<b>A</b>) GCs were transfected with or without HIF-1α siRNA for 12 h and then cultured under hypoxia or normoxia. Protein levels of LC3, p62, and BNIP3 were detected by Western blot. (<b>B</b>) Quantitative analysis of LC3-I to LC3-II conversion. Data represent the mean ± SD; <span class="html-italic">n</span> ≥ 3; **** <span class="html-italic">p</span> &lt; 0.0001; *** <span class="html-italic">p</span> &lt; 0.001; ns, not significant. (<b>C</b>) Quantitative analysis of BNIP3 and p62 protein levels. Data represent the mean ± SD; <span class="html-italic">n</span> ≥ 3; **** <span class="html-italic">p</span> &lt; 0.0001; *** <span class="html-italic">p</span> &lt; 0.001; * <span class="html-italic">p</span> &lt; 0.05. (<b>D</b>) Cells were transfected with or without HIF-1α siRNA for 12 h, treated with or without 15 mM Nala, and cultured for an additional 12 h. Protein levels of LC3, p62, and BNIP3 were analyzed. (<b>E</b>) Quantitative analysis of LC3-I to LC3-II conversion. Data represent the mean ± SD; <span class="html-italic">n</span> ≥ 3; **** <span class="html-italic">p</span> &lt; 0.0001. (<b>F</b>) Quantitative analysis of BNIP3 and p62 protein levels. Data represent the mean ± SD; <span class="html-italic">n</span> ≥ 3; **** <span class="html-italic">p</span> &lt; 0.0001; *** <span class="html-italic">p</span> &lt; 0.001; ** <span class="html-italic">p</span> &lt; 0.01; * <span class="html-italic">p</span> &lt; 0.05. (<b>G</b>) Immunofluorescence localization of GFP-LC3 in granulosa cells. (<b>H</b>) Quantification of GFP-LC3 puncta per cell. Data represent the mean ± SD; *** <span class="html-italic">p</span> &lt; 0.001; * <span class="html-italic">p</span> &lt; 0.05. At least 5 cells were counted per group. Error bars represent the standard deviation of the mean.</p>
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<p>Knockdown of BNIP3 inhibits lactate-induced autophagy under hypoxia. (<b>A</b>) GCs were transfected with or without BNIP3 siRNA for 12 h and then cultured under hypoxia or normoxia. Protein levels of LC3 and p62 were detected by Western blot. (<b>B</b>) Quantitative analysis of LC3-I to LC3-II conversion. Data represent the mean ± SD; <span class="html-italic">n</span> ≥ 3; **** <span class="html-italic">p</span> &lt; 0.0001. (<b>C</b>) Quantitative analysis of p62 protein levels. Data represent the mean ± SD; <span class="html-italic">n</span> ≥ 3; **** <span class="html-italic">p</span> &lt; 0.0001; *** <span class="html-italic">p</span> &lt; 0.001. (<b>D</b>) GCs transfected with or without BNIP3 siRNA for 12 h were treated with or without 15 mM Nala and cultured for an additional 12 h. Protein levels of LC3 and p62 were analyzed. (<b>E</b>) Quantitative analysis of LC3-I to LC3-II conversion. Data represent the mean ± SD; <span class="html-italic">n</span> ≥ 3; **** <span class="html-italic">p</span> &lt; 0.0001; * <span class="html-italic">p</span> &lt; 0.05. (<b>F</b>) Quantitative analysis of p62 protein levels. Data represent the mean ± SD; <span class="html-italic">n</span> ≥ 3; **** <span class="html-italic">p</span> &lt; 0.0001; ** <span class="html-italic">p</span> &lt; 0.01. (<b>G</b>) Immunofluorescence localization of GFP-LC3 in GCs. (<b>H</b>) Quantification of GFP-LC3 puncta per cell. Data represent the mean ± SD; **** <span class="html-italic">p</span> &lt; 0.0001; * <span class="html-italic">p</span> &lt; 0.05. At least 5 cells were counted per group. Error bars represent the standard deviation of the mean.</p>
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<p>Hypoxia and lactate trigger BNIP3 to disrupt the Bcl-2/Beclin-1 complex, activating Beclin-1-dependent autophagy. (<b>A</b>) Cells cultured under hypoxia or normoxia were immunoprecipitated with an anti-BNIP3 antibody, and the precipitates were analyzed by immunoblotting to assess protein expression levels. (<b>B</b>) Quantitative analysis of Beclin-1 protein levels. Data represent the mean ± SD; <span class="html-italic">n</span> ≥ 3; * <span class="html-italic">p</span> &lt; 0.05. (<b>C</b>) Quantitative analysis of Bcl-2 protein levels. Data represent the mean ± SD; <span class="html-italic">n</span> ≥ 3; ** <span class="html-italic">p</span> &lt; 0.01. (<b>D</b>) Cells were treated with 15 mM 2-DG or 15 mM oxamate and exposed to hypoxia or normoxia for 2 h. Following treatment, cells were immunoprecipitated using an anti-BNIP3 antibody, and protein expression levels were analyzed by immunoblotting. (<b>E</b>) Quantitative analysis of Beclin-1 protein levels. Data represent the mean ± SD; <span class="html-italic">n</span> ≥ 3; *** <span class="html-italic">p</span> &lt; 0.001; ** <span class="html-italic">p</span> &lt; 0.01. (<b>F</b>) Quantitative analysis of Bcl-2 protein levels. Data represent the mean ± SD; <span class="html-italic">n</span> ≥ 3; **** <span class="html-italic">p</span> &lt; 0.0001. (<b>G</b>) After lactate inhibition using 3 mM α-CHCA for 2 h, cells were supplemented with Nala and cultured under normoxia for 12 h. Cells were immunoprecipitated with an anti-BNIP3 antibody, and protein expression levels of the precipitates were analyzed by immunoblotting. (<b>H</b>) Quantitative analysis of Beclin-1 protein levels. Data represent the mean ± SD; <span class="html-italic">n</span> ≥ 3; **** <span class="html-italic">p</span> &lt; 0.0001. (<b>I</b>) Quantitative analysis of Bcl-2 protein levels. Data represent the mean ± SD; <span class="html-italic">n</span> ≥ 3; **** <span class="html-italic">p</span> &lt; 0.0001. Error bars represent the standard deviation of the mean.</p>
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<p>Schematic diagram illustrating the molecular mechanism by which lactate promotes granulosa cell autophagy via the HIF-1α/BNIP3/Beclin-1 signaling pathway. Under hypoxic conditions, lactate activates the HIF-1α/BNIP3/Beclin-1 pathway, leading to upregulation of BNIP3. BNIP3 promotes granulosa cell autophagy by competitively binding to Bcl-2, thereby increasing the availability of free Beclin-1 to initiate the autophagic process.</p>
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11 pages, 599 KiB  
Review
Probiotic Bacterium-Derived p40, p75, and HM0539 Proteins as Novel Postbiotics and Gut-Associated Immune System (GAIS) Modulation: Postbiotic-Gut-Health Axis
by Feray Gençer Bingöl, Duygu Ağagündüz and Ferenc Budán
Microorganisms 2025, 13(1), 23; https://doi.org/10.3390/microorganisms13010023 - 26 Dec 2024
Abstract
It is known that probiotics have direct and indirect effects on many systems in the body, especially the gastrointestinal system. Interest in using probiotic strain-derived cell components and metabolites has also increased as a result of the significant benefits of probiotics. Although many [...] Read more.
It is known that probiotics have direct and indirect effects on many systems in the body, especially the gastrointestinal system. Interest in using probiotic strain-derived cell components and metabolites has also increased as a result of the significant benefits of probiotics. Although many terminologies and definitions are used for these components and metabolites, the International Scientific Association of Probiotics and Prebiotics (ISAPP) recommended the use of the term postbiotic in 2021, which is defined as “a preparation of inanimate microorganisms and/or their components that confers a health benefit on the host”. Postbiotics are bioactive metabolites such as organic acids, peptides/proteins, cell wall components, functional enzymes, short-chain fatty acids, vitamins, and phenols. These molecules mediate many positive effects such as immunomodulatory, antimicrobial, and antioxidant effects. These positive effects on maintaining health have enabled the identification of many new postbiotic proteins such as p40, p75, and HM0539. In this review, the postbiotic proteins p40, p75, and HM0539 derived from lactobacilli and their functional effects are systematically summarized. The p40 protein, in particular, has been shown to support gut barrier activity and reduce inflammation, potentially through mechanisms involving epidermal growth factor receptor-dependent signaling. Additionally, p40 and p75 proteins exhibit protective effects on intestinal epithelial tight junctions, suggesting their therapeutic potential in preventing intestinal damage and diseases such as colitis. HM0539 enhances intestinal barrier integrity, exhibits antiinflammatory properties, and protects against bacterial infection, suggesting its possible as a therapeutic for inflammatory bowel disease. This review may contribute to future studies on the therapeutic use of p40, p75, and HM0539 postbiotic proteins in inflammatory gastrointestinal system diseases. Full article
(This article belongs to the Special Issue Interactions Between Probiotics and Host)
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Figure 1
<p>Schematic representation of various health effects of p40, p75, and HM0539 in the host. Created with <a href="http://BioRender.com" target="_blank">BioRender.com</a>.</p>
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