[go: up one dir, main page]

 
 
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

Article Types

Countries / Regions

remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline

Search Results (1,780)

Search Parameters:
Keywords = JAK

Order results
Result details
Results per page
Select all
Export citation of selected articles as:
29 pages, 18284 KiB  
Article
Enhancing Cellular Homeostasis: Targeted Botanical Compounds Boost Cellular Health Functions in Normal and Premature Aging Fibroblasts
by Ramona Hartinger, Khushboo Singh, Jesse Leverett and Karima Djabali
Biomolecules 2024, 14(10), 1310; https://doi.org/10.3390/biom14101310 - 16 Oct 2024
Viewed by 394
Abstract
The human skin, the body’s largest organ, undergoes continuous renewal but is significantly impacted by aging, which impairs its function and leads to visible changes. This study aimed to identify botanical compounds that mimic the anti-aging effects of baricitinib, a known JAK1/2 inhibitor. [...] Read more.
The human skin, the body’s largest organ, undergoes continuous renewal but is significantly impacted by aging, which impairs its function and leads to visible changes. This study aimed to identify botanical compounds that mimic the anti-aging effects of baricitinib, a known JAK1/2 inhibitor. Through in silico screening of a botanical compound library, 14 potential candidates were identified, and 7 were further analyzed for their effects on cellular aging. The compounds were tested on both normal aged fibroblasts and premature aging fibroblasts derived from patients with Hutchinson–Gilford Progeria Syndrome (HGPS). Results showed that these botanical compounds effectively inhibited the JAK/STAT pathway, reduced the levels of phosphorylated STAT1 and STAT3, and ameliorated phenotypic changes associated with cellular aging. Treatments improved cell proliferation, reduced senescence markers, and enhanced autophagy without inducing cytotoxicity. Compounds, such as Resveratrol, Bisdemethoxycurcumin, Pinosylvin, Methyl P-Hydroxycinnamate, cis-Pterostilbene, and (+)-Gallocatechin, demonstrated significant improvements in both control and HGPS fibroblasts. These findings suggest that these botanical compounds have the potential to mitigate age-related cellular alterations, offering promising strategies for anti-aging therapies, particularly for skin health. Further in vivo studies are warranted to validate these results and explore their therapeutic applications. Full article
(This article belongs to the Section Natural and Bio-derived Molecules)
Show Figures

Figure 1

Figure 1
<p>The screening workflow used in virtual screening. Out of approximately 48,000 phytochemicals in the database, 2000 molecules showed a docking score above −6 kcal/mol for JAK-2. Among these, about 1500 molecules exhibited docking scores above −6 kcal/mol for JAK-1. Following this initial screening, approximately 275 phytochemicals were selected based on drug-likeness criteria (Lipinski rule of 5). From this subset, 21 molecules were prioritized for experimental validation.</p>
Full article ">Figure 2
<p>Detection of JAK-STAT inhibition by candidate botanical compounds. (<b>A</b>–<b>N</b>) P-STAT protein levels in control fibroblasts (5757C, SNS 15%) were quantified after treatment with specified botanical compounds for 3 days. Western blots are shown in <a href="#app1-biomolecules-14-01310" class="html-app">Figure S1</a>. The levels of P-STAT1 and P-STAT3 were quantified using Western blot analyses and normalized to GAPDH. Bars marked with a red cross (+) indicate concentrations at which the compounds exhibited cytotoxic effect, as evidenced by increased cell death compared to mock-treated counterparts.</p>
Full article ">Figure 3
<p>Cumulative population doubling (CPD) was measured after 7 days of long-term treatment with botanical compounds at indicated various different concentrations in control fibroblasts (representative strain 5757C, SNS~15%). Mock-treated control cells are depicted in black.</p>
Full article ">Figure 4
<p>Cumulative population doubling (CPD) and percentage of dead cells in control and HGPS fibroblasts. Control fibroblast (strains 5757C, 5567A, F369, M368) and HGPS fibroblast (strains P003, P127, P271) cultures with a senescence level of ~15% were grown and treated under varying conditions for 7 days. The treatment groups included no compound (mock), 2.5 μM (+)-Pinoresinol (S), 10 μM Resveratrol (R), 2 μM Bisdemethoxycurcumin (B), 1 μM Pinosylvin (P), 1.5 μM Methyl P-Hydroxycinnamate (M), 2.5 μM cis-Pterostilbene (Z), and 10 μM (+)-Gallocatechin (C). (<b>A</b>) Population doubling determined on day 7 of cultivation. (<b>B</b>) Percentage of dead cells on day 7 of cultivation. (<b>A</b>,<b>B</b>) Values are presented as mean ± SD (n = 4 for control, n = 3 for HGPS); * <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; assessed using unpaired <span class="html-italic">t</span>-test and one-way anova.</p>
Full article ">Figure 5
<p>Replicative senescence levels and cell cycle profiles of control and HGPS fibroblasts under different compound treatment conditions. Control fibroblasts (strains 5757C, 5567A, F369, M368) and HGPS fibroblasts (strains P003, P127, P271) with a senescence level of ~15% were cultured and treated for 7 days with the following: no compound (mock), 2.5 μM (+)-Pinoresinol (S), 10 μM Resveratrol (R), 2 μM Bisdemethoxycurcumin (B), 1 μM Pinosylvin (P), 1.5 μM Methyl P-Hydroxycinnamate (M), 2.5 μM cis-Pterostilbene (Z), and 10 μM (+)-Gallocatechin (C). (<b>A</b>) Percentage of senescent cells in control and HGPS groups (Control: n = 4, HGPS: n = 3). (<b>B</b>) Cell cycle profiles of control and HGPS groups. Relative percentages of cells in the G0/G1, S, and G2/M phases are shown. DNA was stained with propidium iodine (PI) (Control: n = 4, HGPS: n = 3). (<b>C</b>) Representative images of Western blot analyses for p16 and p21 proteins in total protein extracts. Normalized to GAPDH. Original western blots can be found at <a href="#app1-biomolecules-14-01310" class="html-app">Figure S3</a>. (<b>D</b>,<b>E</b>) Quantification of p16 and p21 protein levels normalized to GAPDH (<b>E</b>). Graphs display means ± SD (Control and HGPS n = 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; 0.0001; assessed using unpaired <span class="html-italic">t</span>-test and one-way anova.</p>
Full article ">Figure 6
<p>Western blot analysis of control and HGPS fibroblasts treated with botanical compounds. Control fibroblasts (5757C, 5567A, F369, M368) and HGPS fibroblasts (P003, P127, P271) with a senescence level of approximately 15% were treated for 7 days with no compound (mock), 2.5 μM (+)-Pinoresinol (S), 10 μM Resveratrol (R), 2 μM Bisdemethoxycurcumin (B), 1 μM Pinosylvin (P), 1.5 μM Methyl P-Hydroxycinnamate (M), 2.5 μM cis-Pterostilbene (Z), and 10 μM (+)-Gallocatechin (C). Panels (<b>A</b>,<b>C</b>,<b>E</b>,<b>G</b>) show representative Western blot images for phosphorylated and total forms of STAT1 (<b>A</b>), STAT3 (<b>C</b>), AMPK (<b>E</b>), and NFκB (<b>G</b>) from three experiments (n = 3). Panels (<b>B</b>,<b>D</b>,<b>F</b>,<b>H</b>) depict the ratios of phosphorylated to total STAT1 (<b>B</b>), STAT3 (<b>D</b>), AMPK (<b>F</b>), and NFκB (<b>H</b>) in both control and HGPS fibroblasts. Original western blots can be found at <a href="#app1-biomolecules-14-01310" class="html-app">Figure S3</a>. Graphs present mean ± SD; significance indicated by * <span class="html-italic">p</span> &lt; 0.05; ** <span class="html-italic">p</span> &lt; 0.01; *** <span class="html-italic">p</span> &lt; 0.001; and **** <span class="html-italic">p</span> &lt; 0.0001, using an unpaired <span class="html-italic">t</span>-test and one-way anova.</p>
Full article ">Figure 7
<p>Assessment of ROS and autophagy levels in control and HGPS Fibroblasts. Control fibroblasts (5757C, 5567A, F369, M368) and HGPS fibroblasts (P003, P127, P271) with a senescence level of approximately 15% were treated for 7 days with no compound (mock) and with varying concentrations of the following botanical compounds: 2.5 μM (+)-Pinoresinol (S), 10 μM Resveratrol (R), 2 μM Bisdemethoxycurcumin (B), 1 μM Pinosylvin (P), 1.5 μM Methyl P-Hydroxycinnamate (M), 2.5 μM cis-Pterostilbene (Z), and 10 μM (+)-Gallocatechin (C). (<b>A</b>) Intracellular ROS levels were determined by measuring oxidized dichlorofluorescein (DCF) using the DCFDA cellular ROS detection assay (n = 3). (<b>B</b>) Autophagy levels were analyzed by measuring monodansylcadaverine (MDC) via fluorescence photometry (n = 3). (<b>C</b>,<b>E</b>) Representative Western blot images for p62 (<b>C</b>) and LC3B (<b>E</b>). (<b>D</b>) Quantification of p62 protein levels normalized to GAPDH (n = 3). Original western blots can be found at <a href="#app1-biomolecules-14-01310" class="html-app">Figure S4</a>. (<b>F</b>) Ratio of LC3B-II to LC3B-I (n = 3). Graphs show mean ± SD; significance levels are indicated by * (<span class="html-italic">p</span> &lt; 0.05), ** (<span class="html-italic">p</span> &lt; 0.01), *** (<span class="html-italic">p</span> &lt; 0.001), and **** (<span class="html-italic">p</span> &lt; 0.0001), analyzed using an unpaired <span class="html-italic">t</span>-test and one-way anova.</p>
Full article ">Figure 8
<p>Heatmap illustrates the effects of botanical compounds on various cellular functions and pathways in control and HGPS fibroblasts. Dark green indicates significant amelioration, light green represents non-significant amelioration, orange denotes a non-significant negative effect, and grey indicates no change.</p>
Full article ">
11 pages, 754 KiB  
Article
Multigene Panel Next-Generation Sequencing Techniques in the Management of Patients with Metastatic Colorectal Carcinoma: The Way Forward for Personalized Treatment? A Single-Center Experience
by Laura Matteucci, Francesco Giulio Sullo, Chiara Gallio, Luca Esposito, Margherita Muratore, Ilario Giovanni Rapposelli, Daniele Calistri, Elisabetta Petracci, Claudia Rengucci, Laura Capelli, Elisa Chiadini, Paola Ulivi, Alessandro Passardi and Alessandro Bittoni
Int. J. Mol. Sci. 2024, 25(20), 11071; https://doi.org/10.3390/ijms252011071 (registering DOI) - 15 Oct 2024
Viewed by 237
Abstract
The efficacy and cost-effectiveness of Multigene Panel Next-Generation Sequencing (NGS) in directing patients towards genomically matched therapies remain uncertain. This study investigated metastatic colorectal cancer (mCRC) patients who underwent NGS analysis on formalin-fixed paraffin-embedded tumor samples. Data from 179 patients were analyzed, revealing [...] Read more.
The efficacy and cost-effectiveness of Multigene Panel Next-Generation Sequencing (NGS) in directing patients towards genomically matched therapies remain uncertain. This study investigated metastatic colorectal cancer (mCRC) patients who underwent NGS analysis on formalin-fixed paraffin-embedded tumor samples. Data from 179 patients were analyzed, revealing no mutations in 39 patients (21.8%), one mutation in 83 patients (46.4%), and two or more mutations in 57 patients (31.8%). KRAS mutations were found in 87 patients (48.6%), including KRAS G12C mutations in 5 patients (2.8%), PIK3CA mutations in 40 patients (22.4%), and BRAF mutations in 26 patients (14.5%). Less common mutations were identified: ERBB2 in five patients (2.8%) and SMO in four patients (2.2%). Additionally, MAP2K1, CTNNB1, and MYC were mutated in three patients (2.4%). Two mutations (1.1%) were observed in ERBB3, RAF1, MTOR, JAK1, and FGFR2. No significant survival differences were observed based on number of mutations. In total, 40% of patients had druggable molecular alterations, but only 1.1% received genomically guided treatment, suggesting limited application in standard practice. Despite this, expanded gene panel testing can identify actionable mutations, aiding personalized treatment strategies in metastatic CRC, although current eligibility for biomarker-guided trials remains limited. Full article
Show Figures

Figure 1

Figure 1
<p>Pie chart of the number of alterations per patient.</p>
Full article ">Figure 2
<p>Kaplan–Meier curves for progression-free survival (<b>left</b>) and overall survival (<b>right</b>) based on the mutational status of <span class="html-italic">BRAF</span> gene.</p>
Full article ">
14 pages, 3697 KiB  
Article
Efficacy and Potential Mechanisms of Naringin in Atopic Dermatitis
by Seung-Ah Yoo, Ki-Chan Kim and Ji-Hyun Lee
Int. J. Mol. Sci. 2024, 25(20), 11064; https://doi.org/10.3390/ijms252011064 (registering DOI) - 15 Oct 2024
Viewed by 254
Abstract
Atopic dermatitis (AD) is one of the most prevalent chronic inflammatory skin diseases. Topical treatments are recommended for all patients regardless of severity, making it essential to develop an effective topical AD treatment with minimal side effects; We investigated the efficacy of topical [...] Read more.
Atopic dermatitis (AD) is one of the most prevalent chronic inflammatory skin diseases. Topical treatments are recommended for all patients regardless of severity, making it essential to develop an effective topical AD treatment with minimal side effects; We investigated the efficacy of topical application of naringin in AD and explored the possible mechanisms using an AD mouse model induced by 1-chloro-2,4-dinitrobenzene (DNCB). Clinical, histological, and immunological changes related to AD and Janus kinase (JAK)-signal transducer and activator of transcription (STAT) signaling proteins in the skin tissues were measured as outcomes; Naringin treatment resulted in a significant improvement in dermatitis severity score and reduced epidermal thickness and mast cell count in the skin (p < 0.05). Naringin also demonstrated the ability to inhibit DNCB-induced changes in interleukin (IL) 4, chemokine (C-C motif) ligand (CCL) 17, CCL22, IL1β, interferon-gamma (IFN-γ), and tumor necrosis factor-alpha (TNF-α) levels by quantitative real-time polymerase chain reaction (qRT-PCR) and IL13 by enzyme-linked immunosorbent assay (ELISA) (p < 0.05). Western blot results exhibited the decreased JAK1, JAK2, STAT1, STAT3, phospho-STAT3, and STAT6 expression in the naringin-treated groups (p < 0.05); The findings of this study suggest that topical naringin may effectively improve the symptoms of AD and could be used as a therapeutic agent for AD. Full article
Show Figures

Figure 1

Figure 1
<p>Chemical structures of (<b>A</b>) flavonoid and (<b>B</b>) naringin.</p>
Full article ">Figure 2
<p>Schematic description of the experiment (n = 6 per group). DNCB, 1-chloro-2,4-dinitrobenzene.</p>
Full article ">Figure 3
<p>(<b>A</b>) Clinical images of the ear and back at the end of the challenge period (day 16). (<b>B</b>) Graphs representing dermatitis severity and ear thickness assessment results. Values represent the mean ± SEM (n = 6). Data compared among multiple groups were analyzed using one-way analysis of variance. * <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 compared to the NC or DNCB-only group. DNCB, 1-chloro-2,4-dinitrobenzene; NC, normal control.</p>
Full article ">Figure 4
<p>(<b>A</b>) Pathology images of H&amp;E and toluidine blue staining in dorsal skin tissue samples. Mast cells are stained purple with toluidine blue. Original magnification = ×200, scale bar = 100 μm. (<b>B</b>) Graphs representing the epidermal thickness and the number of mast cells. Values are mean ± SEM (n = 6). Data compared among multiple groups were analyzed using one-way analysis of variance. *** <span class="html-italic">p</span> &lt; 0.001 compared to the NC or DNCB-only group. H&amp;E, hematoxylin and eosin; NC, normal control; DNCB, 1-chloro-2,4-dinitrobenzene.</p>
Full article ">Figure 5
<p>Expressed mRNA level of (<b>A</b>) TNF-α, (<b>B</b>) IFN-γ, (<b>C</b>) IL4, (<b>D</b>) CCL17, (<b>E</b>) CCL22, (<b>F</b>) IL1β, (<b>G</b>) IL31, and (<b>H</b>) TSLP quantified by qRT-PCR and (<b>I</b>) IL13 by ELISA in dorsal skin tissues. The expression of each gene was normalized to that of Actb. Each qRT-PCR reaction was performed in triplicate. Values are mean ± SEM (n = 6). Data compared among multiple groups were analyzed using one-way analysis of variance. * <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 compared to the NC or DNCB-only group. CCL, chemokine C-C motif ligand; DNCB, 1-chloro-2,4-dinitrobenzene; IL, interleukin; INF-γ, interferon-gamma; NC, normal control; TNF-α, tumor necrosis factor-alpha; TSLP, thymic stromal lymphopoietin.</p>
Full article ">Figure 6
<p>Expression of JAK–STAT proteins in dorsal skin tissues. Immunoblotting intensities were calculated with ImageJ software (version 1.8.0). Values are mean ± SEM (n = 6). Data compared among multiple groups were analyzed using one-way analysis of variance. * <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 compared to the NC or DNCB-only group. DNCB, 1-chloro-2,4-dinitrobenzene; JAK-STAT, Janus kinase-signal transducer and activator of transcription; NC, normal control; P-STAT3, phospho-STAT3.</p>
Full article ">
15 pages, 2671 KiB  
Review
Pathophysiology, Treatment, and Prognosis of Thrombocytopenia, Anasarca, Fever, Reticulin Fibrosis/Renal Failure, and Organomegaly (TAFRO) Syndrome: A Review
by Takuya Kakutani, Riko Kamada and Yotaro Tamai
Curr. Issues Mol. Biol. 2024, 46(10), 11255-11269; https://doi.org/10.3390/cimb46100668 - 9 Oct 2024
Viewed by 344
Abstract
TAFRO syndrome, first reported in 2010, is a systemic inflammatory disease with a rapid onset and potentially fatal course if not treated promptly and appropriately. The name is derived from the initial letters describing the characteristic symptoms of thrombocytopenia, anasarca, fever, reticulin fibrosis/renal [...] Read more.
TAFRO syndrome, first reported in 2010, is a systemic inflammatory disease with a rapid onset and potentially fatal course if not treated promptly and appropriately. The name is derived from the initial letters describing the characteristic symptoms of thrombocytopenia, anasarca, fever, reticulin fibrosis/renal failure, and organomegaly. It is sometimes considered a special subtype of idiopathic multicentric Castleman disease (iMCD) because lymph node biopsies often reveal the pathology findings seen in iMCD. However, its clinical manifestations and prognoses are not well documented. Since the clinical manifestations and prognoses of TAFRO syndrome differ significantly from those of iMCD, it is recognized as an independent disease concept and considered to partially overlap with the pathology of MCD. The pathogenesis of TAFRO syndrome remains largely unknown. Due to the lack of appropriate treatment, it often presents with multiple organ dysfunction and fatality. In this review, we summarized new findings on the pathogenesis of TAFRO syndrome and discussed current effective therapies and future treatment strategies. Full article
(This article belongs to the Collection Molecular Mechanisms in Human Diseases)
Show Figures

Figure 1

Figure 1
<p>Classification of MCD and TAFRO syndrome. iMCD-TAFRO syndrome is classified as a combination of cases that present with symptoms similar to TAFRO syndrome and have histological evaluations that reveal MCD-like findings and cases that do not undergo histological evaluations and exclude other diseases similar to TAFRO syndrome.</p>
Full article ">Figure 2
<p>The 2015 disease severity classification for TAFRO syndrome. Minor update added in 2019.</p>
Full article ">Figure 3
<p>Diagnostic criteria for TAFRO syndrome created in 2021.</p>
Full article ">Figure 4
<p>Diagnostic algorithm for TAFRO syndrome.</p>
Full article ">Figure 5
<p>Pathophysiology and potential therapeutic targets in TAFRO syndrome (other than IL-6 pathway).</p>
Full article ">Figure 6
<p>IL-6 signaling pathway and therapeutic targets.</p>
Full article ">
27 pages, 4023 KiB  
Article
Leveraging Therapeutic Proteins and Peptides from Lumbricus Earthworms: Targeting SOCS2 E3 Ligase for Cardiovascular Therapy through Molecular Dynamics Simulations
by Nasser Alotaiq, Doni Dermawan and Nasr Eldin Elwali
Int. J. Mol. Sci. 2024, 25(19), 10818; https://doi.org/10.3390/ijms251910818 - 8 Oct 2024
Viewed by 460
Abstract
Suppressor of cytokine signaling 2 (SOCS2), an E3 ubiquitin ligase, regulates the JAK/STAT signaling pathway, essential for cytokine signaling and immune responses. Its dysregulation contributes to cardiovascular diseases (CVDs) by promoting abnormal cell growth, inflammation, and resistance to cell death. This study aimed [...] Read more.
Suppressor of cytokine signaling 2 (SOCS2), an E3 ubiquitin ligase, regulates the JAK/STAT signaling pathway, essential for cytokine signaling and immune responses. Its dysregulation contributes to cardiovascular diseases (CVDs) by promoting abnormal cell growth, inflammation, and resistance to cell death. This study aimed to elucidate the molecular mechanisms underlying the interactions between Lumbricus-derived proteins and peptides and SOCS2, with a focus on identifying potential therapeutic candidates for CVDs. Utilizing a multifaceted approach, advanced computational methodologies, including 3D structure modeling, protein–protein docking, 100 ns molecular dynamics (MD) simulations, and MM/PBSA calculations, were employed to assess the binding affinities and functional implications of Lumbricus-derived proteins on SOCS2 activity. The findings revealed that certain proteins, such as Lumbricin, Chemoattractive glycoprotein ES20, and Lumbrokinase-7T1, exhibited similar activities to standard antagonists in modulating SOCS2 activity. Furthermore, MM/PBSA calculations were employed to assess the binding free energies of these proteins with SOCS2. Specifically, Lumbricin exhibited an average ΔGbinding of −59.25 kcal/mol, Chemoattractive glycoprotein ES20 showed −55.02 kcal/mol, and Lumbrokinase-7T1 displayed −69.28 kcal/mol. These values suggest strong binding affinities between these proteins and SOCS2, reinforcing their potential therapeutic efficacy in cardiovascular diseases. Further in vitro and animal studies are recommended to validate these findings and explore broader applications of Lumbricus-derived proteins. Full article
Show Figures

Figure 1

Figure 1
<p>Three-dimensional structural modeling results illustrating proteins and peptides derived from earthworms of the <span class="html-italic">Lumbricus</span> genus. (<b>a</b>) Cytochrome b. (<b>b</b>) SCBP3 protein. (<b>c</b>) Lumbricin. (<b>d</b>) Chemoattractive glycoprotein ES20. (<b>e</b>) Histone H3. (<b>f</b>) Lumbrokinase-7T1. Three proteins exhibit well-folded, globular structures, while another three display large, unfolded regions or loops, indicating potential structural fluctuations that may influence their interactions with SOCS2 during docking.</p>
Full article ">Figure 2
<p>Molecular docking simulations illustrate the optimal binding orientations for interactions between proteins derived from the earthworm (<span class="html-italic">Lumbricus</span> genus) and SOCS2. (<b>a</b>) SOCS2: EpoR peptide (agonist) complex. (<b>b</b>) SOCS2: N4BP1 (antagonist) complex. (<b>c</b>) SOCS2: Cytochrome b complex. (<b>d</b>) SOCS2: SCBP3 protein complex. (<b>e</b>) SOCS2: Lumbricin complex. (<b>f</b>) SOCS2: Lumbrokinase-7T1 complex.</p>
Full article ">Figure 3
<p>Summary of molecular docking outcomes. (<b>a</b>) Correlation between HADDOCK score and RMSD. (<b>b</b>) Correlation between HADDOCK score and binding affinity. (<b>c</b>) Binding affinity values of the top-performing proteins derived from <span class="html-italic">Lumbricus</span> earthworms, with a threshold of −11.0 kcal/mol. (<b>d</b>) Correlation matrix illustrating the relationship between binding energy (kcal/mol) and individual energy components.</p>
Full article ">Figure 4
<p>An analysis of molecular dynamics (MD) simulations for complexes formed between proteins sourced from the <span class="html-italic">Lumbricus</span> genus earthworm and SOCS2, including several key parameters: (<b>a</b>) the root mean square deviation (RMSD) assessed structural stability, (<b>b</b>) the root mean square fluctuation (RMSF) depicted residue flexibility, (<b>c</b>) the radius of gyration (RoG) illustrated structural compactness, and (<b>d</b>) the number of hydrogen bonds highlighted intermolecular interactions.</p>
Full article ">Figure 5
<p>An analysis of the binding free energy for individual amino acids in SOCS2 interactions with the EpoR peptide (standard agonist), N4BP1 (standard antagonist), and the top three proteins derived from earthworms (<span class="html-italic">Lumbricus</span> genus) using MM/PBSA calculations.</p>
Full article ">
13 pages, 3957 KiB  
Article
Molecular Mechanism of 5,6-Dihydroxyflavone in Suppressing LPS-Induced Inflammation and Oxidative Stress
by Yujia Cao, Yee-Joo Tan and Dejian Huang
Int. J. Mol. Sci. 2024, 25(19), 10694; https://doi.org/10.3390/ijms251910694 - 4 Oct 2024
Viewed by 421
Abstract
5,6-dihydroxyflavone (5,6-DHF), a flavonoid that possesses potential anti-inflammatory and antioxidant activities owing to its special catechol motif on the A ring. However, its function and mechanism of action against inflammation and cellular oxidative stress have not been elucidated. In the current study, 5,6-DHF [...] Read more.
5,6-dihydroxyflavone (5,6-DHF), a flavonoid that possesses potential anti-inflammatory and antioxidant activities owing to its special catechol motif on the A ring. However, its function and mechanism of action against inflammation and cellular oxidative stress have not been elucidated. In the current study, 5,6-DHF was observed inhibiting lipopolysaccharide (LPS)-induced nitric oxide (NO) and cytoplasmic reactive oxygen species (ROS) production with the IC50 of 11.55 ± 0.64 μM and 0.8310 ± 0.633 μM in murine macrophages, respectively. Meanwhile, 5,6-DHF suppressed the overexpression of pro-inflammatory mediators such as proteins and cytokines and eradicated the accumulation of mitochondrial ROS (mtROS). The blockage of the activation of cell surface toll-like receptor 4 (TLR4), impediment of the phosphorylation of c-Jun N-terminal kinase (JNK) and p38 from the mitogen-activated protein kinases (MAPK) pathway, Janus kinase 2 (JAK2) and signal transducer and activator of transcription 3 (STAT3) from the JAK-STAT pathway, and p65 from nuclear factor-κB (NF-κB) pathways were involved in the process of 5,6-DHF suppressing inflammation. Furthermore, 5,6-DHF acted as a cellular ROS scavenger and heme-oxygenase 1 (HO-1) inducer in relieving cellular oxidative stress. Importantly, 5,6-DHF exerted more potent anti-inflammatory activity than its close structural relatives, such as baicalein and chrysin. Overall, our findings pave the road for further research on 5,6-DHF in animal models. Full article
(This article belongs to the Special Issue Cellular Redox Mechanisms in Inflammation and Programmed Cell Death)
Show Figures

Figure 1

Figure 1
<p>Chemical structure of 5,6-DHF (<b>A</b>). Dose response curves of 5,6-DHF on LPS-induced NO production (<b>B</b>) and cell cytotoxicity of 5,6-DHF on RAW 264.7 cells (<b>C</b>). Comparison of the anti-NO activity of 5,6-DHF and its structural analogues at 25 μM (<b>D</b>). The values shown are the mean ± SD of three independent experiments in duplicate. Different letters indicate statistical significance (<span class="html-italic">p</span> &lt; 0.05).</p>
Full article ">Figure 2
<p>The suppressive effects of 5,6-DHF on pro-inflammatory protein expression in LPS-stimulated RAW 264.7 models (<b>A</b>). The expression levels of COX-2 (<b>B</b>), iNOS (<b>C</b>), and TLR4 (<b>D</b>) were determined by Western blot. The inhibitory effects of 5,6-DHF on mRNA expression levels of IL-1β (<b>E</b>), IL-6 (<b>F</b>), and TNF-α (<b>G</b>) tested by qRT-PCR. Data points and bar represent arithmetic means ± SD. Ns, not significant. ** <span class="html-italic">p</span> &lt; 0.01 and **** <span class="html-italic">p</span> &lt; 0.0001 as compared to DMSO group.</p>
Full article ">Figure 3
<p>Effects of 5,6-DHF on MAPK pathway in LPS-induced RAW 264.7 cells (<b>A</b>). Suppressive effects of 5,6-DHF on the LPS-induced p-p38 (<b>B</b>), p-JNK, (<b>C</b>) and p-ERK1/2 (<b>D</b>) expressions and the phosphorylation level of p38 (<b>E</b>), JNK (<b>F</b>), and ERK1/2 (<b>G</b>). All expressions were normalized to that of DMSO treatment. Data points and bar represent arithmetic means ± SD. Ns, not significant. ** <span class="html-italic">p</span> &lt; 0.01 and **** <span class="html-italic">p</span> &lt; 0.0001 as compared to DMSO group.</p>
Full article ">Figure 4
<p>Effects of 5,6-DHF on JAK-STAT pathway in LPS-induced RAW 264.7 cells (<b>A</b>). Suppressive effects of 5,6-DHF on the LPS-induced p-JAK2 (<b>B</b>) and p-STAT3 (<b>C</b>) expression and the phosphorylation level of JAK2 (<b>D</b>) and STAT3 (<b>E</b>). All expressions were normalized to that of DMSO treatment. Data points and bar represent arithmetic means ± SD. Ns, not significant. ** <span class="html-italic">p</span> &lt; 0.01, *** <span class="html-italic">p</span> &lt; 0.001, and **** <span class="html-italic">p</span> &lt; 0.0001 as compared to DMSO group.</p>
Full article ">Figure 5
<p>Effects of 5,6-DHF on NF-κB pathway in LPS-induced RAW 264.7 cells (<b>A</b>); suppressive effects of 5,6-DHF on the LPS-induced p-p65 expression (<b>B</b>); and the phosphorylation level of p65 (<b>C</b>). All expressions were normalized to that of DMSO treatment. Data points and bar represent arithmetic means ± SD. Ns, not significant. * <span class="html-italic">p</span> &lt; 0.05 and ** <span class="html-italic">p</span> &lt; 0.01 as compared to DMSO group.</p>
Full article ">Figure 6
<p>Cellular ROS-scavenging activity of 5,6-DHF on LPS-induced RAW264.7 cells, images were captured by fluorescent microscope (<b>A</b>); blue: cell nuclei stained by H33342; and green: cellular ROS stained by H<sub>2</sub>DCFDA. Dose-response curve of ROS-scavenging activity of 5,6-DHF; scale bar 20 μm (<b>B</b>). Mitochondrial ROS-scavenging activity of 5,6-DHF on LPS-induced RAW264.7 cells (<b>C</b>). The fluorescence was visualized by fluorescent microscopy (blue: cell nuclei stained by H33342; and red: mitochondrial ROS stained by MitoSOX red). The influence of 5,6-DHF on the expression levels of HO-1; scale bar 20 μm (<b>D</b>) Data points and bar represent arithmetic means ± SD. Ns, not significant. *** <span class="html-italic">p</span> &lt; 0.001 and **** <span class="html-italic">p</span> &lt; 0.0001 as compared to DMSO group.</p>
Full article ">Figure 7
<p>Schematic diagram of 5,6-DHF mechanisms in inhibiting LPS-induced inflammatory responses and oxidative stress in RAW 264.7 cells.</p>
Full article ">
15 pages, 2068 KiB  
Article
The G-Protein-Coupled Estrogen Receptor Agonist G-1 Mediates Antitumor Effects by Activating Apoptosis Pathways and Regulating Migration and Invasion in Cervical Cancer Cells
by Abigail Gaxiola-Rubio, Luis Felipe Jave-Suárez, Christian David Hernández-Silva, Adrián Ramírez-de-Arellano, Julio César Villegas-Pineda, Marisa de Jesús Lizárraga-Ledesma, Moisés Ramos-Solano, Carlos Daniel Diaz-Palomera and Ana Laura Pereira-Suárez
Cancers 2024, 16(19), 3292; https://doi.org/10.3390/cancers16193292 - 27 Sep 2024
Viewed by 369
Abstract
Background/Objectives: Estrogens and HPV are necessary for cervical cancer (CC) development. The levels of the G protein-coupled estrogen receptor (GPER) increase as CC progresses, and HPV oncoproteins promote GPER expression. The role of this receptor is controversial due to its anti- and pro-tumor [...] Read more.
Background/Objectives: Estrogens and HPV are necessary for cervical cancer (CC) development. The levels of the G protein-coupled estrogen receptor (GPER) increase as CC progresses, and HPV oncoproteins promote GPER expression. The role of this receptor is controversial due to its anti- and pro-tumor effects. This study aimed to determine the effect of GPER activation, using its agonist G-1, on the transcriptome, cell migration, and invasion in SiHa cells and non-tumorigenic keratinocytes transduced with the HPV16 E6 or E7 oncogenes. Methods: Transcriptome analysis was performed to identify G-1-enriched pathways in SiHa cells. We evaluated cell migration, invasion, and the expression of associated proteins in SiHa, HaCaT-16E6, and HaCaT-16E7 cells using various assays. Results: Transcriptome analysis revealed pathways associated with proliferation/apoptosis (TNF-α signaling, UV radiation response, mitotic spindle formation, G2/M cell cycle, UPR, and IL-6/JAK/STAT), cellular metabolism (oxidative phosphorylation), and cell migration (angiogenesis, EMT, and TGF-α signaling) in SiHa cells. Key differentially expressed genes included PTGS2 (pro/antitumor), FOSL1, TNFRSF9, IL1B, DIO2, and PHLDA1 (antitumor), along with under-expressed genes with pro-tumor effects that may inhibit proliferation. Additionally, DKK1 overexpression suggested inhibition of cell migration. G-1 increased vimentin expression in SiHa cells and reduced it in HaCaT-16E6 and HaCaT-16E7 cells. However, G-1 did not affect α-SMA expression or cell migration in any of the cell lines but increased invasion in HaCaT-16E7 cells. Conclusions: GPER is a promising prognostic marker due to its ability to activate apoptosis and inhibit proliferation without promoting migration/invasion in CC cells. G-1 could potentially be a tool in the treatment of this neoplasia. Full article
(This article belongs to the Special Issue The Estrogen Receptor and Its Role in Cancer)
Show Figures

Figure 1

Figure 1
<p>The identification of differentially expressed genes and enriched pathways modulated by G-1 in the SiHa cell line. (<b>a</b>) A volcano plot illustrating DEGs with fold changes of −2 or lower and 2 or higher, and a <span class="html-italic">p</span>-value of less than 0.05. Red circles on the right indicate upregulated genes, while red circles on the left indicate downregulated genes. (<b>b</b>) An enrichment analysis of the Broad Institute’s Molecular Signature Database Hallmark gene collection was evaluated using the version 4.2.3 of the GSEA software. The left panel shows statistically significant pathway names and the right panel shows the false discovery rate (FDR) and normalized enrichment score (NES) values. The numbers in the bar graph indicate the number of enriched (blue) and non-enriched (pink) genes within each pathway. An FDR &lt; 0.25 was set as the selection criteria. (<b>c</b>) A heatmap of DEGs selected by −2 ≤ Log2 ≥ 2 and a <span class="html-italic">p</span>-value &lt; 0.05. The numbers on the left, shown in red and blue, represent the fold change values. Red numbers indicate gene upregulation, while blue numbers signify gene downregulation. Color coding indicates the detailed analysis of previous publications related to each gene.</p>
Full article ">Figure 2
<p>The effect of GPER activation on the expression of (<b>a</b>) vimentin and (<b>b</b>) αSMA and the induction of (<b>c</b>) migration and (<b>d</b>) invasion in SiHa cell line. This was cultured and stimulated with 1 μM of G-1 for 24 h. Immunofluorescence was performed using a secondary antibody conjugated to FITC (green) and DAPI staining (blue). Merged images are presented at 40×. The migration/invasion assays were performed in transwell chambers. The results are shown as the mean ± SD (**** <span class="html-italic">p</span> ≤ 0.0001; ns: not significant).</p>
Full article ">Figure 3
<p>The effect of GPER activation on the expression of (<b>a</b>) vimentin and (<b>b</b>) αSMA and the induction of (<b>c</b>) migration and (<b>d</b>) invasion in HaCaT-pLVX, HaCaT-16E6, and HaCaT-16E7 cell lines. These were cultured and stimulated with 1μM of G-1 for 24 h. Immunofluorescence was performed using a secondary antibody conjugated to FITC (green) and DAPI staining (blue). Merged images are presented at 40×. The migration/invasion assays were performed in transwell chambers. The results are shown as the mean ± SD (* <span class="html-italic">p</span> ≤ 0.05; ** <span class="html-italic">p</span> ≤ 0.01; *** <span class="html-italic">p</span> ≤ 0.001; ns: not significant).</p>
Full article ">Figure 4
<p>Identification of differentially expressed genes by G-1 in HaCaT-16E7. (<b>a</b>) A volcano plot illustrating DEGs with fold changes of −2 or lower and 2 or higher, and a <span class="html-italic">p</span>-value of less than 0.05. Red circles on the right indicate upregulated genes, while red circles on the left indicate downregulated genes. (<b>b</b>) An enrichment analysis of the Broad Institute’s Molecular Signature Database Hallmark gene collection was evaluated using the version 4.2.3 of the GSEA software. The left panel shows statistically significant pathway names and the right panel shows the false discovery rate (FDR) and normalized enrichment score (NES) values. The numbers in the bar graph indicate the number of enriched (blue) and non-enriched (pink) genes within each pathway. An FDR &lt; 0.25 was set as the selection criteria. (<b>c</b>) A heatmap of DEGs selected by −2 ≤ Log2 ≥ 2 and a <span class="html-italic">p</span>-value &lt; 0.05. The numbers on the left, shown in red and blue, represent the fold change values. Red numbers indicate gene upregulation, while blue numbers signify gene downregulation. Color coding indicates the detailed analysis of previous publications related to each gene.</p>
Full article ">
21 pages, 5846 KiB  
Article
A Proteomic Analysis of Nasopharyngeal Carcinoma in a Moroccan Subpopulation
by Ayman Reffai, Michelle Hori, Ravali Adusumilli, Abel Bermudez, Abdelilah Bouzoubaa, Sharon Pitteri, Mohcine Bennani Mechita and Parag Mallick
Cancers 2024, 16(19), 3282; https://doi.org/10.3390/cancers16193282 - 26 Sep 2024
Viewed by 473
Abstract
Background: Nasopharyngeal carcinoma (NPC) is a distinct cancer of the head and neck that is highly prevalent in Southeast Asia and North Africa. Though an extensive analysis of environmental and genetic contributors has been performed, very little is known about the proteome of [...] Read more.
Background: Nasopharyngeal carcinoma (NPC) is a distinct cancer of the head and neck that is highly prevalent in Southeast Asia and North Africa. Though an extensive analysis of environmental and genetic contributors has been performed, very little is known about the proteome of this disease. A proteomic analysis of formalin-fixed paraffin-embedded (FFPE) tissues can provide valuable information on protein expression and molecular patterns for both increasing our understanding of the disease and for biomarker discovery. To date, very few NPC proteomic studies have been performed, and none focused on patients from Morocco and North Africa. Methods: Label-free Liquid Chromatography–Tandem Mass Spectrometry (LC-MS/MS) was used to perform a proteomic analysis of FFPE tissue samples from a cohort of 41 NPC tumor samples of Morocco and North Africa origins. The LC-MS/MS data from this cohort were analyzed alongside 21 healthy controls using MaxQuant 2.4.2.0. A differential expression analysis was performed using the MSstats package in R. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) functional annotations were carried out using the DAVID bioinformatic tool. Results: 3341 proteins were identified across our NPC cases, revealing three main clusters and five DEPs with prognostic significance. The sex disparity of NPC was investigated from a proteomic perspective in which 59 DEPs were found between males and females, with significantly enriched terms associated with the immune response and gene expression. Furthermore, 26 DEPs were observed between patients with early and advanced stages of NPC with a significant cluster related to the immune response, implicating up-regulated DEPs such as IGHA, IGKC, and VAT1. Across both datasets, 6532 proteins were quantified between NPC patients and healthy controls. Among them, 1507 differentially expressed proteins (DEPs) were observed. GO and KEGG pathway analyses showed enriched terms of DEPs related to increased cellular activity, cell proliferation, and survival. PI3K and MAPK proteins as well as RAC1 BCL2 and PPIA were found to be overexpressed between cancer tissues and healthy controls. EBV infection was also one of the enriched pathways implicating its latent genes like LMP1 and LMP2 that activate several proteins and signaling pathways including NF-Kappa B, MAPK, and JAK-STAT pathways. Conclusion: Our findings unveil the proteomic landscape of NPC for the first time in the Moroccan population. These studies additionally may provide a foundation for identifying potential biomarkers. Further research is still needed to help develop tools for the early diagnosis and treatment of NPC in Moroccan and North African populations. Full article
Show Figures

Figure 1

Figure 1
<p>Label-free quantification shotgun proteomics workflow of nasopharyngeal carcinoma employed in this study.</p>
Full article ">Figure 2
<p>Protein identification and quantification in NPC and healthy control samples. (<b>a</b>): The Venn diagram showing the identified and overlapping proteins between NPC cases and healthy controls; (<b>b</b>): The heatmap of the label-free quantification protein abundances across all samples.</p>
Full article ">Figure 3
<p>Protein quantification and clustering in NPC samples. (<b>a</b>) The heatmap of the label-free quantification protein abundances across all NPC samples. (<b>b</b>) The silhouette plot representing the 3 identified clusters.</p>
Full article ">Figure 4
<p>Volcano plots showing the differentially expressed proteins with an absolute 1 log2 fold change and <span class="html-italic">p</span>-value ≤ 0.05 among the following: (<b>a</b>). the NPC cluster condition (cluster 1 vs. 2, cluster 1 vs. 3, and cluster 2 vs. 3); (<b>b</b>). early versus advanced stage condition; (<b>c</b>). male versus female condition; and (<b>d</b>). NPC case versus control condition.</p>
Full article ">Figure 5
<p>Gene Ontology enrichment analysis of DEPs observed between patients with early and advanced stages of NPC. BP-, CC-, and MF-enriched terms are presented.</p>
Full article ">Figure 6
<p>Pathway analysis of DEPs observed between male and female patients. (<b>a</b>). Gene Ontology enrichment analysis. Enriched terms of biological process, cellular component, and molecular function are presented. (<b>b</b>). Enriched terms of KEGG pathway analysis are presented.</p>
Full article ">Figure 7
<p>Pathway analysis of DEPs observed between NPC cases and healthy controls. (<b>a</b>). Gene Ontology enrichment analysis. Twenty most significant enriched terms of biological process, cellular component, and molecular function are presented. (<b>b</b>). KEGG pathway analysis. Twenty most significant enriched pathways are presented.</p>
Full article ">Figure 7 Cont.
<p>Pathway analysis of DEPs observed between NPC cases and healthy controls. (<b>a</b>). Gene Ontology enrichment analysis. Twenty most significant enriched terms of biological process, cellular component, and molecular function are presented. (<b>b</b>). KEGG pathway analysis. Twenty most significant enriched pathways are presented.</p>
Full article ">
41 pages, 3391 KiB  
Review
A Comprehensive Review of Molecular Mechanisms, Pharmacokinetics, Toxicology and Plant Sources of Juglanin: Current Landscape and Future Perspectives
by Magdalena Rutkowska, Martyna Witek and Monika A. Olszewska
Int. J. Mol. Sci. 2024, 25(19), 10323; https://doi.org/10.3390/ijms251910323 - 25 Sep 2024
Viewed by 715
Abstract
Juglanin (kaempferol 3-O-α-L-arabinofuranoside) is a flavonol glycoside occurring in many plants, including its commercial sources Juglans regia, Polygonum aviculare and Selliguea hastata. Recent extensive studies have explored the potential of using juglanin in various pathological conditions, including cardiovascular disorders, [...] Read more.
Juglanin (kaempferol 3-O-α-L-arabinofuranoside) is a flavonol glycoside occurring in many plants, including its commercial sources Juglans regia, Polygonum aviculare and Selliguea hastata. Recent extensive studies have explored the potential of using juglanin in various pathological conditions, including cardiovascular disorders, central nervous and skeletal system disorders, metabolic syndrome, hepatic injury, and cancers. The results indicated a wide range of effects, like anti-inflammatory, anti-oxidant, anti-fibrotic, anti-thrombotic, anti-angiogenic, hepatoprotective, hypolipidemic, hypoglycemic, anti-apoptotic (normal cells), and pro-apoptotic (cancer cells). The health-promoting properties of juglanin can be attributed to its influence on many signaling pathways, associated with SIRT1, AMPK, Nrf2, STING, TLR4, MAPKs, NF-κB, AKT, JAK, and their downstream genes. This review primarily summarizes the current knowledge of molecular mechanisms, pharmacokinetics, biocompatibility, and human use safety of juglanin. In addition, the most promising new plant sources and other existing challenges and prospects have also been reviewed and discussed, aiming to provide direction and rationale for the further development and broader pharmaceutical application of juglanin. Full article
Show Figures

Graphical abstract

Graphical abstract
Full article ">Figure 1
<p>The chemical structure of juglanin.</p>
Full article ">Figure 2
<p>The mechanism of fibrosis with potential grip points for juglanin activity. Abbreviations: collagen type I alpha 1 (COL1A1); collagen type I alpha 2 (COL1A2); connective tissue growth factor (CTGF); chemokine C-X-C motif ligand 1 (CXCL1); extracellular matrix (ECM); fibronectin 1 (FN1); interleukin 17 (IL-17); interleukin 18 (IL-18); interleukin 1β (IL-1β); interleukin 6 (IL-6); mitogen activated protein kinase (MAPK); matrix metalloproteinase 9 (MMP-9); nuclear factor-κB (NF-κB); stimulator of interferon genes (STING); transforming growth factor β1 (TGF-β1); tissue inhibitor of metalloproteinase 1 (TIMP-1); toll-like receptor 4 (TLR4); tumor necrosis factor-α (TNF-α); α-smooth muscle actin (α-SMA).</p>
Full article ">Figure 3
<p>The effects of juglanin on metabolic syndrome. Abbreviations: acetyl-CoA carboxylase α (ACCα); AMP-activated protein kinase (AMPK); carnitine-palmitoyl transferase 1α (CPT-1); CCAAT-enhancer-binding protein α/β (C/EBP α/β); fatty acid synthase (FAS); fatty acid-binding protein 4 (FABP4); glucose transporter 4 (GLUT4); high-density lipoprotein (HDL); nuclear factor-κB (NF-κB); peroxisome proliferator-activated receptor α (PPAR-α); peroxisome proliferator-activated receptor γ (PPAR-γ); sirtuin 1 (SIRT1); stearoyl-CoA desaturase 1 (SCD1); sterol regulatory-element binding proteins 1c (SREBP-1c); triglycerides (TG); tumor necrosis factor-α (TNF-α); uncoupling protein 2 (UCP-2). ↑ increase; ↓ decrease; − not changed.</p>
Full article ">Figure 4
<p>The potential mechanisms of juglanin hepatoprotective activity. Abbreviations: B-cell lymphoma-extra large (Bcl-xL); bcl-2-like protein 4 (Bax); catalase (CAT); glutamate-cysteine ligase subunits (GCLC, GCLM); glutathione peroxides (GPx); interferon β (IFN-β); interleukin 1β (IL-1β); interleukin 6 (IL-6); mitogen-activated protein kinase (MAPK); NAD(P)H quinone dehydrogenase 1 (NQO-1); nuclear factor erythroid 2-related factor 2 (Nrf2); oxygenase 1 (HO-1); phosphorylated signal transducer and activator of transcription (p-STAT); phosphorylated c-Jun N-terminal kinase (p-JNK); phosphorylated extracellular signal-regulated kinase (p-ERK); phosphorylated inhibitor κB-α (p-IκBα); phosphorylated IκB kinase α (p-IKKα); phosphorylated Janus Kinase 2 gene (p-JAK2); phosphorylated nuclear factor-κB (p-NF-κB); phosphorylated TANK-binding kinase 1 (p-TBK1); toll-like receptor 4 (TLR4); reactive oxygen species (ROS); superoxide dismutase (SOD); suppressor of IKKepsilon (SIKE); tumor necrosis factor-α (TNF-α).</p>
Full article ">Figure 5
<p>The potential mechanisms of juglanin activity in the cardiovascular system. Abbreviations: AMP-activated protein kinase (AMPK); endothelial nitric oxide synthase (eNOS); high mobility group box 1 (HMGB1); interleukin 1β (IL-1β); interleukin 6 (IL-6); kruppel-like factor 2 (KLF-2); mitogen-activated protein kinase (MAPK); monocyte chemoattractant protein 1 (MCP-1); NADPH oxidase 2 (NOX-2); nitrogen oxide (NO); nuclear factor erythroid 2-related factor 2 (Nrf2); nuclear factor-κB (NF-κB); oxygenase 1 (HO-1); phosphorylated c-Jun N-terminal kinase (p-JNK); phosphorylated extracellular signal-regulated kinase (p-ERK); reactive oxygen species (ROS); receptor for advanced glycation end products (RAGE); superoxide dismutase (SOD); toll-like receptor 4 (TLR4); tryptophan hydroxylase-1 (TPH-1); tumor necrosis factor-α (TNF-α); vascular cellular adhesion molecule-1 (VCAM-1); vascular endothelial growth factor (VEGF); vascular endothelial growth factor receptor 2 (VEGFR2); zonula occludens-1 (ZO-1).</p>
Full article ">Figure 6
<p>The potential pathways of juglanin activity in the central nervous system. Abbreviations: AMP-activated protein kinase (AMPK); B-cell lymphoma 2 (Bcl-2); Bcl-2-like protein 4 (Bax); beta-amyloid (Aβ); cluster of differentiation 11b (CD11b); cluster of differentiation 14 (CD14); cyclooxygenase 2 (COX-2); enhanced neurotrophic factor (BDNF); glial fibrillary acidic protein (GFAP); inducible nitric oxide synthase (iNOS); interleukin 18 (IL-18); interleukin 1β (IL-1β); interleukin 6 (IL-6); ionized calcium-binding adaptor molecule 1 (Iba1); monocyte chemoattractant protein 1 (MCP-1); myeloid differentiation primary response 88 (MyD88); nuclear factor-κB (NF-κB); phosphoinositide 3-kinase (PI3K); phosphorylated inhibitor κB-α (p-IκBα); phosphorylated IκB kinase α (p-IKKα); phosphorylated microtubule-associated protein (p-Tau); poly-ADP-ribose polymerase (PARP); protein kinase B (AKT); toll-like receptor 4 (TLR4); tumor necrosis factor-α (TNF-α).</p>
Full article ">Figure 7
<p>The potential pathways of juglanin activity in the skeletal system. Abbreviations: apoptosis-associated Speck-like protein containing a caspase activation and recruitment domain (ASC); cysteine cathepsin K (CTSK); disintegrin and metalloproteinase with thrombospondin motifs (ADAMTS); factor matrix metalloproteinase (MMP); factor matrix metalloproteinase 9 (MMP-9); glutathione (GSH); interleukin 1 (IL-1); interleukin 1β (IL-1β); interleukin 6 (IL-6); malondialdehyde (MDA); NADPH oxidase 4 (NOX-4); nitrogen oxide (NO); nucleotide-binding domain, leucine-rich–containing family, pyrin domain–containing-3 (NLRP3); nuclear factor-κB (NF-κB); phosphorylated inhibitor κB-α (p-IκBα); phosphorylated IκB kinase (p-IKK); prostaglandin E2 (PGE2); reactive oxygen species (ROS); receptor activator for nuclear factor κ B (RANK); receptor activator for nuclear factor κ B ligand (RANKL); sirtuin 1 (SIRT1); superoxide dismutase (SOD); thioredoxin-interacting protein (TxNIP); transcription factor nuclear factor of activated T cells c1 (NFATc1); Fos proto-oncogene (c-Fos); transforming growth factor β (TGF-β); translating ribosome affinity purification (TRAP); tumor necrosis factor receptor-associated factor 6 (TRAF6); tumor necrosis factor-α (TNF-α).</p>
Full article ">Figure 8
<p>The potential metabolic pathways of juglanin anti-cancer activity. Abbreviations: ataxia telangiectasia mutated (ATM); autophagy protein 7, 3 (ATG-7, ATG-3); B-cell lymphoma 2 (Bcl-2); B-cell lymphoma-extra large (Bcl-xL); bcl-2-like protein 4 (Bax); BH3 domain-containing protein (Bad); cyclin-dependent kinase 1 (CDK1); death receptor 4 (DR4); death receptor 5 (DR5); FAS-associated death domain protein (FADD); gap 2 phase/mitosis phase in the cell cycle (G2/M); interleukin 18 (IL-18); interleukin 1β (IL-1β); microtubule-associated protein light chain 3 (LC3); nuclear factor-κB (NF-κB); phosphatidylinositol 3-kinase catalytic subunit type 3 (PIK3C3); phosphoinositide 3-kinase (PI3K); phosphorylated cell division cycle 2 (p-Cdc2); phosphorylated cell division cycle 25C (p-Cdc25C); phosphorylated checkpoint kinase 2 (p-Chk2); phosphorylated c-Jun N-terminal kinase (p-JNK); phosphorylated extracellular signal-regulated kinase 1/2 (p-ERK 1/2); phosphorylated inhibitor κB-α (p-IκBα); phosphorylated mammalian target of rapamycin (p-mTOR); poly-ADP-ribose polymerase (PARP); protein kinase B (AKT); reactive oxygen species (ROS); TNF-related apoptosis-inducing ligand (TRAIL); tumor necrosis factor-α (TNF-α).</p>
Full article ">Figure 9
<p>Summary of the potential pathways of juglanin’s biological activity. Abbreviations: AMP-activated protein kinase (AMPK); high mobility group box 1 (HMGB1); Janus kinase gene/signal transducer and activator of transcription (JAK/STAT); Kruppel-like factor 2 (KLF-2); mitogen-activated protein kinase (MAPK); nuclear factor erythroid 2-related factor 2 (Nrf2); nuclear factor-κB (NF-κB); nucleotide-binding domain, leucine-rich-containing family, pyrin domain-containing-3 (NLRP3); phosphoinositide 3-kinase/protein kinase B (PI3K/AKT); sirtuin 1 (SIRT1); stimulator of interferon genes (STING); toll-like receptor 4 (TLR4); transforming growth factor β1 (TGF- β1).</p>
Full article ">
21 pages, 22151 KiB  
Article
Impact of SDF-1 and AMD3100 on Hair Follicle Dynamics in a Chronic Stress Model
by Yinglin Zhao, Wenzi Liang, Zhehui Liu, Xiuwen Chen and Changmin Lin
Biomolecules 2024, 14(10), 1206; https://doi.org/10.3390/biom14101206 - 25 Sep 2024
Viewed by 448
Abstract
Chronic stress is a common cause of hair loss, involving inflammatory responses and changes in cellular signaling pathways. This study explores the mechanism of action of the SDF-1/CXCR4 signaling axis in chronic stress-induced hair loss. The research indicates that SDF-1 promotes hair follicle [...] Read more.
Chronic stress is a common cause of hair loss, involving inflammatory responses and changes in cellular signaling pathways. This study explores the mechanism of action of the SDF-1/CXCR4 signaling axis in chronic stress-induced hair loss. The research indicates that SDF-1 promotes hair follicle growth through the PI3K/Akt and JAK/STAT signaling pathways. Transcriptome sequencing analysis was conducted to identify differentially expressed genes in the skin of normal and stressed mice, with key genes SDF-1/CXCR4 selected through machine learning and a protein-protein interaction network established. A chronic stress mouse model was created, with injections of SDF-1 and AMD3100 administered to observe hair growth, weight changes, and behavioral alterations and validate hair follicle activity. Skin SDF-1 concentrations were measured, differentially expressed genes were screened, and pathways were enriched. Activation of the PI3K/Akt and JAK/STAT signaling pathways was assessed, and siRNA technology was used in vitro to inhibit the expression of SDF-1 or CXCR4. SDF-1 promoted hair follicle activity, with the combined injection of SDF-1 and AMD3100 weakening this effect. The activation of the PI3K/Akt and JAK/STAT signaling pathways was observed in the SDF-1 injection group, confirmed by Western blot and immunofluorescence. Silencing SDF-1 through siRNA-mediated inhibition reduced cell proliferation and migration abilities. SDF-1 promotes hair growth in chronic stress mice by activating the PI3K/Akt and JAK/STAT pathways, an effect reversible by AMD3100. The SDF-1/CXCR4 axis may serve as a potential therapeutic target for stress-induced hair loss. Full article
Show Figures

Figure 1

Figure 1
<p>Effects of CUS on body weight, behavioral traits, and hair growth in mice. Note: (<b>A</b>) Comparison of body weight between two groups of mice; (<b>B</b>) Representative images and statistical graphs of open field and tail suspension tests for the two groups of mice; (<b>C</b>) Typical images and statistical graphs comparing hair coverage between the two groups of mice; (<b>D</b>) Comparison of hair length between the two groups of mice. Each group consisted of <span class="html-italic">n</span> = 6 mice; * indicates <span class="html-italic">p</span> &lt; 0.05 compared to the Control group.</p>
Full article ">Figure 2
<p>Assessment of chronic stress impact on gene expression and signaling pathway activity in mouse skin. Note: (<b>A</b>) Volcano plot demonstrating 2650 differentially expressed genes between the chronic stress group and the normal group of mice. Each point represents a gene, with position indicating the magnitude of expression change and statistical significance; (<b>B</b>) Heat map showing the most significant differentially expressed genes in mice under chronic stress; (<b>C</b>) Dot plot revealing enrichment of differentially expressed genes in biological processes such as stress response, inflammation, cell migration, and activation of inflammatory cells; (<b>D</b>) Enrichment analysis of KEGG pathways displayed in a dot plot showing the enrichment status of differentially expressed genes in various pathways, where the size of the dots represents the number of involved genes and the color intensity reflects the significance of enrichment.</p>
Full article ">Figure 3
<p>The key role of SDF−1 gene and its interaction network analysis under chronic stress. Note: (<b>A</b>) Genes highly correlated with chronic stress-induced hair loss selected through Lasso regression analysis; (<b>B</b>) Results from the random forest model demonstrating the high importance score of SDF−1/CXCR4 among all evaluated genes, further supporting its role as a critical regulatory factor in chronic stress-induced hair loss; (<b>C</b>) PPI network showcasing interactions between SDF−1/CXCR4 and multiple signaling pathway proteins, particularly with proteins interacting with CXCR4 receptor.</p>
Full article ">Figure 4
<p>Impact of SDF-1 and AMD3100 on hair growth in CUS mice. Note: (<b>A</b>) ELISA analysis of SDF-1 concentration in the serum of mice in each group; (<b>B</b>) Immunofluorescence observation of the colocalization of SFD-1 and CXCR4 in mouse skin tissue (Scale bar: 25 μm); (<b>C</b>) Typical images and statistical graphs comparing hair coverage, hair length, and the proportion of skin area in the growth phase among the mouse groups; (<b>D</b>) Typical images and statistical graphs from H&amp;E staining observation of the follicle count, proportion of follicles in the growth and regression phases among the mouse groups, labelled as 100/25 μm in the figures. Each group consisted of <span class="html-italic">n</span> = 6 mice; * indicates <span class="html-italic">p</span> &lt; 0.05.</p>
Full article ">Figure 5
<p>Impact of SDF-1 and AMD3100 on the protein expression of PI3K/Akt and JAK/STAT signaling pathways. Note: (<b>A</b>) Representative immunofluorescence images and statistical analysis of the PI3K/Akt signaling pathway in mouse skin tissue for each group, with a scale bar of 50 μm; (<b>B</b>) Representative immunofluorescence images and statistical analysis of the JAK/STAT signaling pathway in mouse skin tissue for each group; (<b>C</b>) Representative Western blot images and statistical analysis of the PI3K/Akt and JAK/STAT signaling pathways in mouse skin tissue for each group. Each group consisted of <span class="html-italic">n</span> = 6 mice; * indicates <span class="html-italic">p</span> &lt; 0.05.</p>
Full article ">Figure 6
<p>Effects of SDF-1 gene silencing on the expression and function of skin cells in mice under chronic stress. Note: (<b>A</b>) Bright-field microscopy (Scale bar: 50 μm) and immunofluorescence identification (Scale bar: 25 μm) of primary cell extraction and purification; (<b>B</b>) Western blot and RT-qPCR experiments examining the expression levels of SDF-1 mRNA and protein in mouse back skin cells after SDF-1 siRNA treatment. Original images can be found in <a href="#app1-biomolecules-14-01206" class="html-app">Supplementary File 1</a>; (<b>C</b>) Immunofluorescence showing the colocalization of SDF-1 and CXCR4 in skin cells, with a scale bar of 50 μm; (<b>D</b>) Western blot analysis of p-PI3K/PI3K expression levels; (<b>E</b>) Representative images and statistical results of the cell wound healing test; (<b>F</b>) Assessment of cell proliferation using CCK-8 assay. * indicates significant differences between the two groups (<span class="html-italic">p</span> &lt; 0.05), with all cell experiments repeated six times.</p>
Full article ">Figure 7
<p>Molecular mechanisms of the SDF-1/CXCR4 signaling axis in chronic stress-induced hair loss in mice.</p>
Full article ">
17 pages, 803 KiB  
Review
TRIM25, TRIM28 and TRIM59 and Their Protein Partners in Cancer Signaling Crosstalk: Potential Novel Therapeutic Targets for Cancer
by De Chen Chiang and Beow Keat Yap
Curr. Issues Mol. Biol. 2024, 46(10), 10745-10761; https://doi.org/10.3390/cimb46100638 - 25 Sep 2024
Viewed by 552
Abstract
Aberrant expression of TRIM proteins has been correlated with poor prognosis and metastasis in many cancers, with many TRIM proteins acting as key oncogenic factors. TRIM proteins are actively involved in many cancer signaling pathways, such as p53, Akt, NF-κB, MAPK, TGFβ, JAK/STAT, [...] Read more.
Aberrant expression of TRIM proteins has been correlated with poor prognosis and metastasis in many cancers, with many TRIM proteins acting as key oncogenic factors. TRIM proteins are actively involved in many cancer signaling pathways, such as p53, Akt, NF-κB, MAPK, TGFβ, JAK/STAT, AMPK and Wnt/β-catenin. Therefore, this review attempts to summarize how three of the most studied TRIMs in recent years (i.e., TRIM25, TRIM28 and TRIM59) are involved directly and indirectly in the crosstalk between the signaling pathways. A brief overview of the key signaling pathways involved and their general cross talking is discussed. In addition, the direct interacting protein partners of these TRIM proteins are also highlighted in this review to give a picture of the potential protein–protein interaction that can be targeted for future discovery and for the development of novel therapeutics against cancer. This includes some examples of protein partners which have been proposed to be master switches to various cancer signaling pathways. Full article
(This article belongs to the Section Biochemistry, Molecular and Cellular Biology)
Show Figures

Figure 1

Figure 1
<p>TRIM25, TRIM28 and TRIM59 in the signaling crosstalk between p53, Akt, NF-κB, MAPK p38, TGFβ, AMPK, JAK/STAT and Wnt/β-catenin pathways. For simplicity, only crosstalk that directly involves the interacting protein partners of TRIM25, TRIM28 and TRIM59 are shown in the diagram.</p>
Full article ">
19 pages, 11922 KiB  
Article
The Potential Related Genes and Mechanisms Involved in Improving the Treadmill Exercise Ability of APP/PS1 Mice
by Zhe Zhao, Xingqing Wu, Weijia Wu, Yingzhe Tang, Xiangyuan Meng, Mei Peng, Changfa Tang, Lan Zheng and Wenfeng Liu
Int. J. Mol. Sci. 2024, 25(19), 10244; https://doi.org/10.3390/ijms251910244 - 24 Sep 2024
Viewed by 368
Abstract
Alzheimer’s disease (AD) causes a decline in skeletal muscle function, which can further exacerbate the cognitive dysfunction of patients with AD. It has been widely established that exercise improves AD brain pathology, but the role of skeletal muscle in AD is still poorly [...] Read more.
Alzheimer’s disease (AD) causes a decline in skeletal muscle function, which can further exacerbate the cognitive dysfunction of patients with AD. It has been widely established that exercise improves AD brain pathology, but the role of skeletal muscle in AD is still poorly understood. In this study, we investigated the effects of treadmill exercise on the exercise ability of APP/PS1 transgenic AD mice and explored potential gene expression changes in their skeletal muscle. The APP/PS1 mice were subjected to a treadmill exercise for 12 weeks, followed by the Morris water maze and the open field test. After behavioral experiments, the changes in morphology, area, collagen fiber deposition, and ultrastructure of the skeletal muscle were determined; the balance of skeletal muscle protein synthesis and decomposition was analyzed; and changes in gene expression were investigated using RNA-Seq. We found that this exercise strategy can promote the learning and memory abilities of AD mice, reduce their anxiety-like behavior, improve their exercise ability, alleviate skeletal muscle atrophy, and optimize the microstructure. It can also enhance skeletal muscle protein synthesis and decomposition and improve several signaling pathways, such as the JAK–STAT, Wnt, and NOD-like receptors while decreasing calcium, cAMP, cGMP–PKG, and other signaling pathways. Six KEGG enrichment signaling pathways were downregulated and five signaling pathways were upregulated in the AD mice compared with wild-type mice, and these pathways were precisely reversed after the treadmill exercise. The expression of transcription factors such as Fosb and Egr1 in the skeletal muscle of AD mice decreased, followed by a decrease in the regulated target genes Socs1, Srrm4, and Il1b, a trend that was reversed following the exercise intervention. After exercise, AD mice exhibited a similar gene expression to that of wild-type mice, indicating enhanced exercise ability. The potential regulatory pathways and related genes identified in this study provide valuable insights for the clinical management and treatment of AD. Full article
(This article belongs to the Special Issue Exercise and Health: Cellular and Molecular Perspectives)
Show Figures

Figure 1

Figure 1
<p>Treadmill exercise improved memory and reduced the anxiety behavior of AD mice: (<b>A</b>) changes in the latency period observed using the Morris water maze; (<b>B</b>) numbers of times the platform was crossed in the Morris water maze; (<b>C</b>) total swimming distance in the Morris water maze; (<b>D</b>) swimming tracks in the Morris water maze, with the circle in the southwest quadrant showing the location of the platform; (<b>E</b>) total distance traversed in the open field test; (<b>F</b>) time taken to traverse the central area in the open field test; (<b>G</b>) percentage of distance in the central area in the open field test; (<b>H</b>) representative images of moving tracks in the open field test, in which the small squares were added when statistical analysis was performed (<span class="html-italic">n</span> = 10). Data are expressed as the means ± SD; # <span class="html-italic">p</span> &lt; 0.05 and ## <span class="html-italic">p</span> &lt; 0.01 compared to the WTC group; * <span class="html-italic">p</span> &lt; 0.05 and ** <span class="html-italic">p</span> &lt; 0.01 compared to the ADC group.</p>
Full article ">Figure 2
<p>Treadmill exercise improved the exercise ability and alleviated the skeletal muscle atrophy of AD mice: (<b>A</b>) total running distance until exhaustion; (<b>B</b>) total running time until exhaustion; (<b>C</b>) speed at the point of exhaustion (<span class="html-italic">n</span> = 4); (<b>D</b>) percentage of HE-stained skeletal muscle cross-sectional area; (<b>E</b>) HE staining, WGA staining, Masson staining, and representative microscopic images under a transmission electron microscope for observed skeletal muscle (<span class="html-italic">n</span> = 3). Data are expressed as the means ± SD; ## <span class="html-italic">p</span> &lt; 0.01 compared to the WTC group; ** <span class="html-italic">p</span> &lt; 0.01 compared to the ADC group.</p>
Full article ">Figure 3
<p>Treadmill exercise increased the expressions of genes and proteins involved in skeletal muscle protein synthesis in the AD mice: (<b>A</b>) mouse skeletal muscle IGF-1 mRNA expression; (<b>B</b>) mouse skeletal muscle PI3K mRNA expression; (<b>C</b>) mouse skeletal muscle AKT mRNA expression; (<b>D</b>) mouse skeletal muscle mTOR mRNA expression; (<b>E</b>) representative images of Western blotting of PI3K, p-PI3K, AKT, and p-AKT; (<b>F</b>) relative expression of PI3K protein; (<b>G</b>) relative expression of p-PI3K protein; (<b>H</b>) relative expression of AKT protein; (<b>I</b>) relative expression of p-AKT protein (<span class="html-italic">n</span> = 6). Data are expressed as the means ± SD; # <span class="html-italic">p</span> &lt; 0.05 and ## <span class="html-italic">p</span> &lt; 0.01 compared to the WTC group; * <span class="html-italic">p</span> &lt; 0.05 and ** <span class="html-italic">p</span> &lt; 0.01 compared to the ADC group.</p>
Full article ">Figure 4
<p>Treadmill exercise increased the expressions of genes and proteins related to skeletal muscle protein degradation in the AD mice: (<b>A</b>) mouse skeletal muscle Fbxo 25 mRNA expression; (<b>B</b>) mouse skeletal muscle Fbxo 32 mRNA expression; (<b>C</b>) mouse skeletal muscle MAFbx mRNA expression; (<b>D</b>) mouse skeletal muscle Murf mRNA expression; (<b>E</b>) mouse skeletal muscle At9a mRNA expression; (<b>F</b>) mouse skeletal muscle Beclin mRNA expression; (<b>G</b>) mouse skeletal muscle p62 mRNA expression; (<b>H</b>) mouse skeletal muscle LC3 mRNA expression; (<b>I</b>) representative images of the Western blotting of Fbxo 32 and Murf; (<b>J</b>) relative expression of Fbxo 32 protein; (<b>K</b>) relative expression of Murf protein (<span class="html-italic">n</span> = 6). Data are expressed as the mean ± SD; # <span class="html-italic">p</span> &lt; 0.05 and ## <span class="html-italic">p</span> &lt; 0.01 compared to the WTC group; * <span class="html-italic">p</span> &lt; 0.05 and ** <span class="html-italic">p</span> &lt; 0.01 compared to the ADC group.</p>
Full article ">Figure 5
<p>Treadmill exercise altered the gene expression in the skeletal muscle of the AD mice: (<b>A</b>) volcano plot of the DEGs in the ADC group versus the WTC group; (<b>B</b>) volcano plot of the DEGs in the ADE group versus the ADC group; (<b>C</b>) heatmap of the DEGs in the ADC group versus the WTC group; (<b>D</b>) heatmap of the DEGs in the ADE group versus the ADC group (<span class="html-italic">n</span> = 3).</p>
Full article ">Figure 6
<p>GO enrichment analysis of the DEGs: (<b>A</b>) GO enrichment analysis of downregulated genes in the ADC group compared to the WTC group; (<b>B</b>) GO enrichment analysis of upregulated genes in the ADC group compared to the WTC group; (<b>C</b>) GO enrichment analysis of downregulated genes in the ADE group compared to the ADC group; (<b>D</b>) GO enrichment analysis of upregulated genes in the ADE group compared to the ADC group (<span class="html-italic">n</span> = 3).</p>
Full article ">Figure 6 Cont.
<p>GO enrichment analysis of the DEGs: (<b>A</b>) GO enrichment analysis of downregulated genes in the ADC group compared to the WTC group; (<b>B</b>) GO enrichment analysis of upregulated genes in the ADC group compared to the WTC group; (<b>C</b>) GO enrichment analysis of downregulated genes in the ADE group compared to the ADC group; (<b>D</b>) GO enrichment analysis of upregulated genes in the ADE group compared to the ADC group (<span class="html-italic">n</span> = 3).</p>
Full article ">Figure 7
<p>The KEGG enrichment analysis of the DEGs: (<b>A</b>) The KEGG enrichment analysis of downregulated genes in the ADC group compared to the WTC group; (<b>B</b>) the KEGG enrichment analysis of upregulated genes in the ADC group compared to the WTC group; (<b>C</b>) the KEGG enrichment analysis of downregulated genes in the ADE group compared to the ADC group; (<b>D</b>) the KEGG enrichment analysis of upregulated genes in the ADE group compared to the ADC group (<span class="html-italic">n</span> = 3).</p>
Full article ">Figure 8
<p>Differential transcription factor–target gene Sankey diagram. (<b>A</b>) Transcription factor changes in ADC group compared with WTC group. (<b>B</b>) Changes in transcription factors in ADE group compared with ADC group. From left to right: first column—transcription factor families; second column—differential transcription factors; third column—differential target genes. The middle line indicates the correspondence of transcription factor families, transcription factors, and target genes. The genes in blue are downregulated, while the genes in red are upregulated (<span class="html-italic">n</span> = 3).</p>
Full article ">Figure 9
<p>Program of exercise ability test.</p>
Full article ">
12 pages, 971 KiB  
Review
Current Understanding of Cardiovascular Calcification in Patients with Chronic Kidney Disease
by Sijie Chen, Rining Tang and Bicheng Liu
Int. J. Mol. Sci. 2024, 25(18), 10225; https://doi.org/10.3390/ijms251810225 - 23 Sep 2024
Viewed by 645
Abstract
The burden of chronic kidney disease (CKD) is increasing, posing a serious threat to human health. Cardiovascular calcification (CVC) is one of the most common manifestations of CKD, which significantly influences the morbidity and mortality of patients. The manifestation of CVC is an [...] Read more.
The burden of chronic kidney disease (CKD) is increasing, posing a serious threat to human health. Cardiovascular calcification (CVC) is one of the most common manifestations of CKD, which significantly influences the morbidity and mortality of patients. The manifestation of CVC is an unusual accumulation of mineral substances containing calcium and phosphate. The main component is hydroxyapatite. Many cells are involved in this process, such as smooth muscle cells (SMCs) and endothelial cells. CVC is an osteogenic process initiated by complex mechanisms such as metabolic disorders of calcium and phosphorus minerals, inflammation, extracellular vesicles, autophagy, and micro-RNAs with a variety of signaling pathways like Notch, STAT, and JAK. Although drug therapy and dialysis technology continue to advance, the survival time and quality of life of CVC patients still face challenges. Therefore, early diagnosis and prevention of CKD-related CVC, reducing its mortality rate, and improving patients’ quality of life have become urgent issues in the field of public health. In this review, we try to summarize the state-of-the-art understanding of the progression of CVC and hope that it will help in the prevention and treatment of CVC in CKD. Full article
(This article belongs to the Special Issue Signaling Pathways and Novel Therapies in Heart Disease)
Show Figures

Figure 1

Figure 1
<p>The mechanism diagram of CVC. P: phosphorus, PTH: parathyroidhormone, IS: Indoxylsulfate, VSMCs: vascular smooth muscle cells, miRNAs: micro-RNAs, EVs: extracellular vesicles, Runx2: runt-related transcription factor 2, BMP2: bone morphogenetic protein, TNF: tumor necrosis factor, IL: interleukin, ROS: reactive oxygen species, EndMT: endothelial-to-mesenchymal transition, STAT: transcriptional activation factor, NICD: Notch intracellular domain.</p>
Full article ">
15 pages, 6085 KiB  
Article
The Anti-Vitiligo Effects of Feshurin In Vitro from Ferula samarcandica and the Mechanism of Action
by Mayire Nueraihemaiti, Zang Deng, Khamidulla Kamoldinov, Niu Chao, Maidina Habasi and Haji Akber Aisa
Pharmaceuticals 2024, 17(9), 1252; https://doi.org/10.3390/ph17091252 - 23 Sep 2024
Viewed by 584
Abstract
Background: Vitiligo is a complex disorder characterized by skin depigmentation; the canonical Wnt signaling pathway that involves β-catenin plays a crucial role in promoting the melanin production in melanocytes. Targeted inhibition of the Janus kinase JAK-STAT pathway can effectively diminish the secretion [...] Read more.
Background: Vitiligo is a complex disorder characterized by skin depigmentation; the canonical Wnt signaling pathway that involves β-catenin plays a crucial role in promoting the melanin production in melanocytes. Targeted inhibition of the Janus kinase JAK-STAT pathway can effectively diminish the secretion of the chemokine C-X-C motif ligand CXCL10, thereby safeguarding melanocytes. Ferula has been applied as a treatment regimen for a long period; however, its use for the treatment of vitiligo has not been previously documented. Methods: CCK-8 assay, Intracellular melanin content assay, Tyrosinase activity assay, Western blotting, qRT-PCR, and ELISA methods were employed. Using molecular docking verified the inhibitory effects of feshurin on the JAK1. Results: The sesquiterpene coumarin feshurin was separated from Ferula samarcandica. Feshurin was shown to induce GSK-3β phosphorylation, resulting in the translocation of β-catenin into the nucleus. This translocation subsequently upregulated the transcription of microphthalmia-associated transcription factor (MITF), leading to increased tyrosinase activity and melanin production. In addition, feshurin inhibited the production of chemokine CXCL10 via the JAK-STAT signaling pathway, which was verified by molecular docking. Conclusions: Based on these findings, it can be concluded that feshurin exhibits significant potential for the development of novel anti-vitiligo therapeutics. Full article
(This article belongs to the Section Natural Products)
Show Figures

Graphical abstract

Graphical abstract
Full article ">Figure 1
<p>The chemical structure and ultra−performance liquid chromatogram of feshurin (detection wavelength at 254 nm). The Chinese for the horizontal axis is minute.</p>
Full article ">Figure 2
<p>Effects of feshurin on cell viability and morphology. (<b>A</b>,<b>B</b>) The effect of different concentrations (0–200 µM) of feshurin on B16 melanoma and HaCaT cells for 48 h. Cell viability was measured by the CCK-8 assay. (<b>C</b>,<b>D</b>) The morphological changes in the feshurin-treated (0–10 µM) B16 cells and HaCaT cells, as determined by microscopy (100× magnification). (C-NC and D-NC) 0.1% DMSO, (C-1 and D-1) 1 µM, (C-5 and D-5) 5 µM, and (C-10 and D-10) 10 µM of feshurin. CCK-8, cell counting kit-8; DMSO, dimethylsulfoxide; NC, negative control; IFN-γ, interferon-γ; and Rux, ruxolitinib.</p>
Full article ">Figure 3
<p>Effects of feshurin on TYR activity, melanin content, and the melanogenesis-related genes. (<b>A</b>) Presentation of the melanin content following 48 h of treatment with (0–10 μM) of feshurin. (<b>B</b>) TYR activity following 24 h feshurin treatment. (<b>C</b>) Representation of the image indicating the cell precipitation and dissolved solution in the presence of 5% sodium hydroxide. (<b>D</b>,<b>E</b>) The protein levels of MITF, TYR, TRP-1, and TRP-2 were detected following 48 h of feshurin treatment. Photoshop (Adobe Systems, Inc.) was used to determine the protein band density (* <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). The data are shown as the mean ± SD and were analyzed by one-way ANOVA followed by Tukey’s test. All experiments were performed three times. TYR, tyrosinase; MITF, microphthalmia-associated transcription factor; and TRP, tyrosinase-related protein.</p>
Full article ">Figure 4
<p>The compound feshurin activated the Wnt signaling pathway via the phosphorylation of GSK-<span class="html-italic">3β</span>, <span class="html-italic">β</span>-catenin, and AKT. (<b>A</b>,<b>B</b>) The expression levels of melanogenesis-related signaling pathway proteins in the B16 cells treated with (0–10 μM) feshurin for 48 h were analyzed compared with those of <span class="html-italic">β</span>-actin. (<b>C</b>,<b>D</b>) Following the treatment of the B16 cells with DMSO or feshurin (10 μM) for 24 h, the nucleus and cytoplasmic <span class="html-italic">β</span>-catenin expression levels were observed. The cytoplasmic protein levels were standardized against the expression levels of GAPDH and those of the nuclear proteins against the expression levels of lamin B. (<b>E</b>,<b>F</b>) B16 cells were pre-treated with BIO (5 µM) for 2 h and subsequently incubated with feshurin (10 µM) for 24 h to measure the melanin content and TYR activity. Photoshop (Adobe Systems, Inc.) was used to determine the protein band density (* <span class="html-italic">p</span> &lt; 0.05, *** <span class="html-italic">p</span> &lt; 0.001, **** <span class="html-italic">p</span> &lt; 0.0001). The data are shown as the mean ± SD and were analyzed by one-way ANOVA followed by Tukey’s test. All experiments were performed three times. DMSO, dimethylsulfoxide; TYR, tyrosinase; BIO, 6-bromoindirubin-3′-oxime; and SD, standard deviation.</p>
Full article ">Figure 5
<p>Feshurin inhibits the IFN-γ−induced CXCL10 production in HaCaT cells via the JAK-STAT pathway. (<b>A</b>) Following treatment of the HaCaT cells with different concentrations (1–6 μM) of feshurin for 24 h, the expression levels of p-STAT1, JAK-1, and JAK-2 were observed. (Ruxolitinib was used as a positive control and STAT1 phosphorylation was stimulated by IFN-γ.) (<b>B</b>) The expression levels of p-STAT1 were analyzed and compared with those of <span class="html-italic">β</span>-actin. Photoshop (Adobe Systems, Inc.) was used to determine the protein band density. (<b>C</b>) The content of CXCL10 in the cell supernatant was detected by ELISA. (<b>D</b>) RT-qPCR was used to detect the mRNA expression levels of CXCL10. Photoshop was used to determine the protein band density (**** <span class="html-italic">p</span> &lt; 0.0001). The data are shown as the mean ± SD and were analyzed by one-way ANOVA followed by Tukey’s test. All experiments were performed three times. CXCL, chemokine (C-X-C motif) ligand; p-STAT1, phosphorylated-STAT1; JAK, Janus kinase; ELISA, enzyme-linked immunosorbent assay; RT-qPCR, reverse transcription-quantitative PCR; and SD, standard deviation.</p>
Full article ">Figure 6
<p>Molecular docking studies were performed to examine the effects of feshurin on JAK1. A 2D and 3D diagram of non-bonding interactions between feshurin and JAK1. JAK, Janus kinase.</p>
Full article ">
12 pages, 2159 KiB  
Article
Genomic Landscape of Myelodysplastic/Myeloproliferative Neoplasms: A Multi-Central Study
by Fei Fei, Amar Jariwala, Sheeja Pullarkat, Eric Loo, Yan Liu, Parastou Tizro, Haris Ali, Salman Otoukesh, Idoroenyi Amanam, Andrew Artz, Feras Ally, Milhan Telatar, Ryotaro Nakamura, Guido Marcucci and Michelle Afkhami
Int. J. Mol. Sci. 2024, 25(18), 10214; https://doi.org/10.3390/ijms251810214 - 23 Sep 2024
Viewed by 631
Abstract
The accurate diagnosis and classification of myelodysplastic/myeloproliferative neoplasm (MDS/MPN) are challenging due to the overlapping pathological and molecular features of myelodysplastic syndrome (MDS) and myeloproliferative neoplasm (MPN). We investigated the genomic landscape in different MDS/MPN subtypes, including chronic myelomonocytic leukemia (CMML; n = [...] Read more.
The accurate diagnosis and classification of myelodysplastic/myeloproliferative neoplasm (MDS/MPN) are challenging due to the overlapping pathological and molecular features of myelodysplastic syndrome (MDS) and myeloproliferative neoplasm (MPN). We investigated the genomic landscape in different MDS/MPN subtypes, including chronic myelomonocytic leukemia (CMML; n = 97), atypical chronic myeloid leukemia (aCML; n = 8), MDS/MPN-unclassified (MDS/MPN-U; n = 44), and MDS/MPN with ring sideroblasts and thrombocytosis (MDS/MPN-RS-T; n = 12). Our study indicated that MDS/MPN is characterized by mutations commonly identified in myeloid neoplasms, with TET2 (52%) being the most frequently mutated gene, followed by ASXL1 (38.7%), SRSF2 (34.7%), and JAK2 (19.7%), among others. However, the distribution of recurrent mutations differs across the MDS/MPN subtypes. We confirmed that specific gene combinations correlate with specific MDS/MPN subtypes (e.g., TET2/SRSF2 in CMML, ASXL1/SETBP1 in aCML, and SF3B1/JAK2 in MDS/MPN-RS-T), with MDS/MPN-U being the most heterogeneous. Furthermore, we found that older age (≥65 years) and mutations in RUNX1 and TP53 were associated with poorer clinical outcomes in CMML (p < 0.05) by multivariate analysis. In MDS/MPN-U, CBL mutations (p < 0.05) were the sole negative prognostic factors identified in our study by multivariate analysis (p < 0.05). Overall, our study provides genetic insights into various MDS/MPN subtypes, which may aid in diagnosis and clinical decision-making for patients with MDS/MPN. Full article
(This article belongs to the Section Molecular Pathology, Diagnostics, and Therapeutics)
Show Figures

Figure 1

Figure 1
<p>The workflow and study design of our cohort. BM, bone marrow; PB, peripheral blood. (Abbreviations: aCML, atypical myeloid leukemia; AML, acute myeloid leukemia; CMML, chronic myelomonocytic leukemia; MDS/MPN-U, myelodysplastic/myeloproliferative neoplasm-unclassified; and MDS/MPN-RS-T, myelodysplastic/myeloproliferative neoplasm with ring sideroblasts and thrombocytosis.)</p>
Full article ">Figure 2
<p>Frequency of recurrent gene mutations in all myelodysplastic/myeloproliferative neoplasm (MDS/MPN) patients (n = 173).</p>
Full article ">Figure 3
<p>Molecular and cytogenetic characteristics among the different MDS/MPN subtypes (n = 173). An oncoplot showing the mutated genes among the different MDS/MPN subtypes. Each column represents a patient. Thirty-one genes are grouped into eight categories based on their functions: DNA methylation, chromatin modification, RNA splicing, transcription factors, receptor kinases, cohesion, RAS pathways, and others. Green depicts the different MDS/MPN subtypes: CMML, CMML-AML, aCML, MDS/MPN-U, and MDS/MPN-RS-T. Red depicts a single gene mutation; purple depicts more than one mutation in the same gene, mainly corresponding to biallelic <span class="html-italic">TET2</span> mutations. Cytogenetic findings are divided into three groups: normal karyotype, abnormal karyotype, and complex karyotype. Myelofibrosis (MF) status is divided into five groups: MF 0, MF 1, MF 2, MF 3, and N/A. The frequency of recurrent gene mutations among the different MDS/MPN subtypes. (Abbreviations: aCML, atypical myeloid leukemia; AML, acute myeloid leukemia; CMML, chronic myelomonocytic leukemia; MDS/MPN-U, myelodysplastic/myeloproliferative neoplasm-unclassified; MDS/MPN-RS-T, myelodysplastic/myeloproliferative neoplasm with ring sideroblasts and thrombocytosis; MF, myelofibrosis; and N/A, not applicable.)</p>
Full article ">Figure 4
<p>Frequency of mutations based on functional classification among different MDS/MPN subtypes. (<b>A</b>) CMML (n = 97); (<b>B</b>) CMML-AML (n = 12); (<b>C</b>) aCML (n = 8); (<b>D</b>) MDS/MPN-U (n = 44); and (<b>E</b>) MDS/MPN-RS-T (n = 12). (Abbreviations: aCML, atypical myeloid leukemia; AML, acute myeloid leukemia; CMML, chronic myelomonocytic leukemia; MDS/MPN-U, myelodysplastic/myeloproliferative neoplasm-unclassified; and MDS/MPN-RS-T, myelodysplastic/myeloproliferative neoplasm with ring sideroblasts and thrombocytosis).</p>
Full article ">
Back to TopTop