Journal Description
Current Issues in Molecular Biology
Current Issues in Molecular Biology
is an international, scientific, peer-reviewed, open access journal on molecular biology, published monthly online by MDPI (from Volume 43 Issue 1-2021).
- Open Access— free for readers, with article processing charges (APC) paid by authors or their institutions.
- High Visibility: indexed within Scopus, SCIE (Web of Science), PMC, PubMed, Embase, CAPlus / SciFinder, FSTA, AGRIS, and other databases.
- Rapid Publication: manuscripts are peer-reviewed and a first decision is provided to authors approximately 16.8 days after submission; acceptance to publication is undertaken in 2.7 days (median values for papers published in this journal in the first half of 2024).
- Recognition of Reviewers: APC discount vouchers, optional signed peer review, and reviewer names are published annually in the journal.
Impact Factor:
2.8 (2023);
5-Year Impact Factor:
2.9 (2023)
Latest Articles
Identification of NAC Transcription Factors in Suaeda glauca and Their Responses to Salt Stress
Curr. Issues Mol. Biol. 2024, 46(8), 8741-8751; https://doi.org/10.3390/cimb46080516 (registering DOI) - 10 Aug 2024
Abstract
NAC (NAM/ATAF1/2/CUC2) transcription factors regulate plant growth and development and stress responses. Because NAC transcription factors are known to play important roles in the regulation of salt tolerance in many plants, we aimed to explore their roles in the halophyte Suaeda glauca.
[...] Read more.
NAC (NAM/ATAF1/2/CUC2) transcription factors regulate plant growth and development and stress responses. Because NAC transcription factors are known to play important roles in the regulation of salt tolerance in many plants, we aimed to explore their roles in the halophyte Suaeda glauca. Based on transcriptome sequencing data, we identified 25 NAC transcription factor gene family members. In a phylogenetic tree analysis with Arabidopsis thaliana NAC transcription factors, the SgNACs were divided into 10 groups. The physicochemical properties and conserved domains of the putative proteins, as well as the transcript profiles of their encoding genes, were determined for the 25 SgNAC genes using bioinformatic methods. Most of the S. glauca NAC genes were upregulated to some extent after 24 h of salt stress, suggesting that they play an important role in regulating the salt tolerance of S. glauca. These findings lay the foundation for further research on the functions and mechanisms of the NAC gene family in S. glauca.
Full article
(This article belongs to the Special Issue Advances in Multi-Omics for Functional Genomics Studies and Molecular Breeding)
Open AccessArticle
Immunomodulatory Effects of Anadenanthera colubrina Bark Extract in Experimental Autoimmune Encephalomyelitis
by
Karla A. Ramos, Igor G. M. Soares, Larissa M. A. Oliveira, Mariana A. Braga, Pietra P. C. Soares, Gracimerio J. Guarneire, Elaine C. Scherrer, Fernando S. Silva, Nerilson M. Lima, Felipe A. La Porta, Teresinha de Jesus A. S. Andrade, Gagan Preet, Sandra B. R. Castro, Caio César S. Alves and Alessandra P. Carli
Curr. Issues Mol. Biol. 2024, 46(8), 8726-8740; https://doi.org/10.3390/cimb46080515 (registering DOI) - 10 Aug 2024
Abstract
This study aimed to evaluate the efficacy of the ethanolic extract of Anadenanthera colubrina in modulating the immune response in the Experimental Autoimmune Encephalomyelitis (EAE) model. The ethanolic extract of the dried bark was analyzed by ESI (+) Orbitrap-MS to obtain a metabolite
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This study aimed to evaluate the efficacy of the ethanolic extract of Anadenanthera colubrina in modulating the immune response in the Experimental Autoimmune Encephalomyelitis (EAE) model. The ethanolic extract of the dried bark was analyzed by ESI (+) Orbitrap-MS to obtain a metabolite profile, demonstrating a wide variety of polyphenols, such as flavonoids and phenolic acids. Various parameters were evaluated, such as clinical signs, cytokines, cellular profile, and histopathology in the central nervous system (CNS). The ethanolic extract of A. colubrina demonstrated significant positive effects attenuating the clinical signs and pathological processes associated with EAE. The beneficial effects of the extract treatment were evidenced by reduced levels of pro-inflammatory cytokines, such as IL1β, IL-6, IL-12, TNF, IFN-γ, and a notable decrease in several cell profiles, including CD8+, CD4+, CD4+IFN-γ, CD4+IL-17+, CD11c+MHC-II+, CD11+CD80+, and CD11+CD86+ in the CNS. In addition, histological analysis revealed fewer inflammatory infiltrates and demyelination sites in the spinal cord of mice treated with the extract compared to the control model group. These results showed, for the first time, that the ethanolic extract of A. colubrina exerts a modulatory effect on inflammatory processes, improving clinical signs in EAE, in the acute phase of the disease, which could be further explored as a possible therapeutic alternative.
Full article
(This article belongs to the Special Issue Molecular Mechanisms in Demyelinating Disorders and Remyelination Strategies of the CNS)
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![](https://pub.mdpi-res.com/cimb/cimb-46-00515/article_deploy/html/images/cimb-46-00515-g001-550.jpg?1723284468)
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<p>Clinical signs of EAE. Animals (n = 8/group) were monitored daily for clinical signs of EAE after immunization with 100 µg of MOG<sub>35–55</sub> peptide. Mice were treated with 200 mg/kg of the ethanolic extract of <span class="html-italic">A. colubrina</span> barks (EtAc) for six days. The dotted line indicates the start of treatment. Each dot represents the arithmetic mean ± SEM. * indicates <span class="html-italic">p</span> < 0.05 compared to induced and PBS-treated animals (EAE), analyzed by two-way ANOVA with Dunnett’s correction. CN = negative control (not induced and treated with PBS).</p> Full article ">Figure 2
<p>Histopathology of the spinal cord of mice. Histopathology of the spinal cord of mice immunized or not immunized with 100 µg of MOG<sub>35–55</sub> (n = 8/group). Figures are representative of the histological analysis of each experimental group: CN= non-immunized and PBS-treated group (<b>A</b>,<b>B</b>), EAE = immunized and PBS-treated group (<b>C</b>,<b>D</b>), EtAc = immunized and treated with 200 mg/kg ethanolic extract of <span class="html-italic">A. colubrina</span> barks for six days (<b>E</b>,<b>F</b>). The examined groups representative sections (5 µm) were stained with hematoxylin and eosin (H&E) to analyze the cell infiltrate. Original magnification: 10× objective (<b>A</b>,<b>C</b>,<b>E</b>), 40× (<b>B</b>,<b>D</b>,<b>F</b>). Scale bars = 100 µm (10×) and 50 µm (40×). Arrows indicate cellular infiltrates.</p> Full article ">Figure 3
<p>Demyelination of the spinal cord of mice. Histopathology of spinal cords of mice immunized or not immunized with 100 µg of MOG35–55 (n = 8/group). Figures are representative of the histological analysis of each experimental group: CN= non-immunized and PBS-treated group (<b>A</b>), EAE = immunized and PBS-treated group (<b>B</b>), EtAc = immunized and treated with 200 mg/kg ethanolic extract of <span class="html-italic">A. colubrina</span> barks for six days (<b>C</b>). Representative sections (8 µm) of the examined groups, stained with Luxol fast blue, for analysis of the demyelination. Original magnification: 10× objective. Scale bars = 100 µm. Delimited areas = areas of demyelination.</p> Full article ">Figure 4
<p>Cellular profile. Mononuclear cell counts (<b>A</b>,<b>E</b>) and cellular profile determination (<b>B</b>–<b>D</b>,<b>F</b>–<b>H</b>) in the brains (<b>A</b>–<b>D</b>) and spinal cords (<b>E</b>–<b>H</b>) of mice immunized or not immunized with 100 µg of MOG<sub>35–55</sub> (n = 8/group). Mice were treated with 200 mg/kg of the ethanolic extract of <span class="html-italic">A. colubrina</span> barks (EtAc) for six days. Each bar represents the arithmetic mean ± SEM. * indicates <span class="html-italic">p</span> < 0.05 compared to induced and PBS-treated animals (EAE). CN = negative control (not induced and treated with PBS).</p> Full article ">Figure 5
<p>Absolute intensity of the most abundant phenolic acids (cinnamic acid, gallic acid, and <span class="html-italic">p</span>-coumaric acid) and flavonoids (apigenin, catechin, quercetin, and myricetin) annotated through ESI (+) Orbitrap-MS analysis of the ethanolic extract from <span class="html-italic">A. colubrina</span> bark.</p> Full article ">Figure 6
<p>ESI (+) Orbitrap-MS-based metabolite profiling of <span class="html-italic">A. colubrina</span> showing the major classes identified in bark ethanolic extract.</p> Full article ">
<p>Clinical signs of EAE. Animals (n = 8/group) were monitored daily for clinical signs of EAE after immunization with 100 µg of MOG<sub>35–55</sub> peptide. Mice were treated with 200 mg/kg of the ethanolic extract of <span class="html-italic">A. colubrina</span> barks (EtAc) for six days. The dotted line indicates the start of treatment. Each dot represents the arithmetic mean ± SEM. * indicates <span class="html-italic">p</span> < 0.05 compared to induced and PBS-treated animals (EAE), analyzed by two-way ANOVA with Dunnett’s correction. CN = negative control (not induced and treated with PBS).</p> Full article ">Figure 2
<p>Histopathology of the spinal cord of mice. Histopathology of the spinal cord of mice immunized or not immunized with 100 µg of MOG<sub>35–55</sub> (n = 8/group). Figures are representative of the histological analysis of each experimental group: CN= non-immunized and PBS-treated group (<b>A</b>,<b>B</b>), EAE = immunized and PBS-treated group (<b>C</b>,<b>D</b>), EtAc = immunized and treated with 200 mg/kg ethanolic extract of <span class="html-italic">A. colubrina</span> barks for six days (<b>E</b>,<b>F</b>). The examined groups representative sections (5 µm) were stained with hematoxylin and eosin (H&E) to analyze the cell infiltrate. Original magnification: 10× objective (<b>A</b>,<b>C</b>,<b>E</b>), 40× (<b>B</b>,<b>D</b>,<b>F</b>). Scale bars = 100 µm (10×) and 50 µm (40×). Arrows indicate cellular infiltrates.</p> Full article ">Figure 3
<p>Demyelination of the spinal cord of mice. Histopathology of spinal cords of mice immunized or not immunized with 100 µg of MOG35–55 (n = 8/group). Figures are representative of the histological analysis of each experimental group: CN= non-immunized and PBS-treated group (<b>A</b>), EAE = immunized and PBS-treated group (<b>B</b>), EtAc = immunized and treated with 200 mg/kg ethanolic extract of <span class="html-italic">A. colubrina</span> barks for six days (<b>C</b>). Representative sections (8 µm) of the examined groups, stained with Luxol fast blue, for analysis of the demyelination. Original magnification: 10× objective. Scale bars = 100 µm. Delimited areas = areas of demyelination.</p> Full article ">Figure 4
<p>Cellular profile. Mononuclear cell counts (<b>A</b>,<b>E</b>) and cellular profile determination (<b>B</b>–<b>D</b>,<b>F</b>–<b>H</b>) in the brains (<b>A</b>–<b>D</b>) and spinal cords (<b>E</b>–<b>H</b>) of mice immunized or not immunized with 100 µg of MOG<sub>35–55</sub> (n = 8/group). Mice were treated with 200 mg/kg of the ethanolic extract of <span class="html-italic">A. colubrina</span> barks (EtAc) for six days. Each bar represents the arithmetic mean ± SEM. * indicates <span class="html-italic">p</span> < 0.05 compared to induced and PBS-treated animals (EAE). CN = negative control (not induced and treated with PBS).</p> Full article ">Figure 5
<p>Absolute intensity of the most abundant phenolic acids (cinnamic acid, gallic acid, and <span class="html-italic">p</span>-coumaric acid) and flavonoids (apigenin, catechin, quercetin, and myricetin) annotated through ESI (+) Orbitrap-MS analysis of the ethanolic extract from <span class="html-italic">A. colubrina</span> bark.</p> Full article ">Figure 6
<p>ESI (+) Orbitrap-MS-based metabolite profiling of <span class="html-italic">A. colubrina</span> showing the major classes identified in bark ethanolic extract.</p> Full article ">
Open AccessReview
The Enigmas of Tissue Closure: Inspiration from Drosophila
by
Xiaoying Huang, Zhongjing Su and Xiao-Jun Xie
Curr. Issues Mol. Biol. 2024, 46(8), 8710-8725; https://doi.org/10.3390/cimb46080514 (registering DOI) - 9 Aug 2024
Abstract
Hollow structures are essential for development and physiological activity. The construction and maintenance of hollow structures never cease throughout the lives of multicellular animals. Epithelial tissue closure is the main strategy used by living organisms to build hollow structures. The high diversity of
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Hollow structures are essential for development and physiological activity. The construction and maintenance of hollow structures never cease throughout the lives of multicellular animals. Epithelial tissue closure is the main strategy used by living organisms to build hollow structures. The high diversity of hollow structures and the simplicity of their development in Drosophila make it an excellent model for the study of hollow structure morphogenesis. In this review, we summarize the tissue closure processes in Drosophila that give rise to or maintain hollow structures and highlight the molecular mechanisms and distinct cell biology involved in these processes.
Full article
(This article belongs to the Section Biochemistry, Molecular and Cellular Biology)
Open AccessArticle
Assessing the COX-2/PGE2 Ratio and Anti-Nucleosome Autoantibodies as Biomarkers of Autism Spectrum Disorders: Using Combined ROC Curves to Improve Diagnostic Values
by
Afaf El-Ansary, Hanan A. Alfawaz, Abir Ben Bacha and Laila AL-Ayadhi
Curr. Issues Mol. Biol. 2024, 46(8), 8699-8709; https://doi.org/10.3390/cimb46080513 - 8 Aug 2024
Abstract
Autism spectrum disorder (ASD) is a neurodevelopmental condition marked by restricted and repetitive behaviors as well as difficulties with social interaction. Numerous studies have revealed aberrant lipid mediators and autoimmunity as a recognized etiological cause of ASD that is amenable to therapeutic intervention.
[...] Read more.
Autism spectrum disorder (ASD) is a neurodevelopmental condition marked by restricted and repetitive behaviors as well as difficulties with social interaction. Numerous studies have revealed aberrant lipid mediators and autoimmunity as a recognized etiological cause of ASD that is amenable to therapeutic intervention. In this study, the relationship between the relative cyclooxygenase-2/prostaglandin E2 ratio (COX-2/PGE2) as a lipid mediator marker and anti-nucleosome autoantibodies as an autoimmunity marker of ASD was investigated using multiple regression and combined receiver operating characteristic (ROC) curve analyses. The study also sought to identify the linear combination of these variables that optimizes the partial area under the ROC curves. There were forty ASD children and forty-two age- and gender-matched controls included in the current study. Using combined ROC curve analysis, a notable increase in the area under the curve was seen in the patient group, using the control group as a reference group. Additionally, it was reported that the combined markers had improved specificity and sensitivity. This study demonstrates how the predictive value of particular biomarkers associated with lipid metabolism and autoimmunity in children with ASD can be measured using a ROC curve analysis. This technique should help us better understand the etiological mechanism of ASD and how it may adversely affect cellular homeostasis, which is essential to maintaining healthy metabolic pathways. Early diagnosis and intervention may be facilitated by this knowledge.
Full article
(This article belongs to the Special Issue The Role of Prostaglandins in Autism)
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<p>ROC curve for independent COX/PGE2 and anti-nucleosome of patient group according to control group.</p> Full article ">Figure 2
<p>Combined ROC for COX/PGE2 with anti-nucleosome of patient group according to control group.</p> Full article ">Figure 3
<p>Illustrated mechanism of the integrative role of a lower COX-2/PGE2 ratio as a marker of impaired lipid metabolism (1) and higher anti-nucleosome autoantibodies as a marker of autoimmunity (2) in relation to abnormal Wnt signaling (3,4) and glutamate excitotoxicity (5), collectively leading to neuronal death in individuals with ASD. The relative contributions of these signaling pathways (1–5) may account for the heterogeneity and the diverse symptomatology seen in individuals with autism.</p> Full article ">
<p>ROC curve for independent COX/PGE2 and anti-nucleosome of patient group according to control group.</p> Full article ">Figure 2
<p>Combined ROC for COX/PGE2 with anti-nucleosome of patient group according to control group.</p> Full article ">Figure 3
<p>Illustrated mechanism of the integrative role of a lower COX-2/PGE2 ratio as a marker of impaired lipid metabolism (1) and higher anti-nucleosome autoantibodies as a marker of autoimmunity (2) in relation to abnormal Wnt signaling (3,4) and glutamate excitotoxicity (5), collectively leading to neuronal death in individuals with ASD. The relative contributions of these signaling pathways (1–5) may account for the heterogeneity and the diverse symptomatology seen in individuals with autism.</p> Full article ">
Open AccessArticle
Taurine and Polyphenol Complex Repaired Epidermal Keratinocyte Wounds by Regulating IL8 and TIMP2 Expression
by
Sooyeon Lee, Jae Young Shin, Oh Sun Kwon, Seung-Hyun Jun and Nae-Gyu Kang
Curr. Issues Mol. Biol. 2024, 46(8), 8685-8698; https://doi.org/10.3390/cimb46080512 - 8 Aug 2024
Abstract
The healing process after acne lesion extraction provides a miniature model to study skin wound repair mechanisms. In this study, we aimed to identify solutions for acne scars that frequently occur on our faces. We performed acne scar cytokine profiling and found that
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The healing process after acne lesion extraction provides a miniature model to study skin wound repair mechanisms. In this study, we aimed to identify solutions for acne scars that frequently occur on our faces. We performed acne scar cytokine profiling and found that Interleukin 8 (IL8) and Tissue inhibitor of metalloproteinases 2 (TIMP2) were significant factors at the wounded site. The effect of chlorogenic acid and taurine on human epidermal cells and irritated human skin was investigated. Chlorogenic acid and taurine regulated IL8 and TIMP2 expression and accelerated keratinocyte proliferation. Moreover, tight junction protein expression was upregulated by chlorogenic acid and taurine synergistically. Further, these compounds modulated the expression of several inflammatory cytokines (IL1α, IL1β, and IL6) and skin hydration related factor (hyaluronan synthase 3; HAS3). Thus, chlorogenic acid and taurine may exert their effects during the late stages of wound healing rather than the initial phase. In vivo experiments using SLS-induced wounds demonstrated the efficacy of chlorogenic acid and taurine treatment compared to natural healing, reduced erythema, and restored barrier function. Skin ultrasound analysis revealed their potential to promote denser skin recovery. Therefore, the wound-restoring effect of chlorogenic acid and taurine was exerted by suppression of inflammatory cytokines, and induction of cell proliferation, tight junction expression, and remodeling factors.
Full article
(This article belongs to the Section Molecular Pharmacology)
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<p>Comparative analysis of IL8 and TIMP2 expression in normal skin, acne-affected, inflamed, and pigmented sites. IL8 and TIMP2 protein expression were quantified from (1) non-acneic skin, (2) normal skin, (3) sites of inflammation, and (4) sites of pigmentation in acneic skin by ELISA. * <span class="html-italic">p</span> < 0.05 versus control group; Student’s <span class="html-italic">t</span>-test. Data are expressed as the mean ± SEM.</p> Full article ">Figure 2
<p>IL8 and TIMP2 regulatory effects of chlorogenic acid and taurine in cultured HaCaT cells. The synergistic effect of chlorogenic acid and taurine on (<b>A</b>) IL8 inhibition, and (<b>B</b>) TIMP2 activation after 24 h of co-treatment with heat-killed <span class="html-italic">C. acnes</span>. * <span class="html-italic">p</span> < 0.05, ** <span class="html-italic">p</span> < 0.01, *** <span class="html-italic">p</span> < 0.001 relative to the control group; Student’s <span class="html-italic">t</span>-test. Data are expressed as mean ± SEM.</p> Full article ">Figure 3
<p>The synergistic effects of chlorogenic acid and taurine in wound closure and tight junction reinforcement in cultured HaCaT cells. (<b>A</b>) Synergistic wound-healing effect after 24 h treatment with chlorogenic acid and taurine treatment. (<b>B</b>) Upregulated claudin 1 expression after 24 h treatment was analyzed by immunostaining and fluorescence quantification. * <span class="html-italic">p</span> < 0.05, ** <span class="html-italic">p</span> < 0.01, *** <span class="html-italic">p</span> < 0.001 relative to the control group; Student’s <span class="html-italic">t</span>-test. Data are expressed as mean ± SEM.</p> Full article ">Figure 4
<p>Regulatory effects of chlorogenic acid and taurine on inflammatory cytokines and hydration markers. Treatment with chlorogenic acid and taurine for 24 h (<b>A</b>) decreased the mRNA and protein expression level of <span class="html-italic">IL1α</span>, <span class="html-italic">IL1β</span>, and <span class="html-italic">IL6</span>, and (<b>B</b>) increased mRNA and protein expression of <span class="html-italic">HAS3</span> in cultured HaCaT cells. * <span class="html-italic">p</span> < 0.05, ** <span class="html-italic">p</span> < 0.01 relative to the control group; Student’s <span class="html-italic">t</span>-test. Data are expressed as mean ± SEM.</p> Full article ">Figure 5
<p>Attenuation of irritated epidermis and enhancement of dermal density by treatment of chlorogenic acid and taurine. (<b>A</b>) The restorative effect of chlorogenic acid and taurine on an SLS-induced skin wound. ## <span class="html-italic">p</span> < 0.01 relative to treatment with SLS. * <span class="html-italic">p</span> < 0.05, ** <span class="html-italic">p</span> < 0.01 comparing the SLS applied and non-applied group. (<b>B</b>) Increment in epidermal and dermal density by long-term treatment of chlorogenic acid and taurine (yellow arrows: epidermis, red arrows: dermis).* <span class="html-italic">p</span> < 0.05, ** <span class="html-italic">p</span> < 0.01 versus before group; Student’s <span class="html-italic">t</span>-test. Data are expressed as mean ± SEM.</p> Full article ">Figure 6
<p>Summarized effects of chlorogenic acid and taurine in wound-healing effects (<tt>↑</tt>: activation, <tt>↓</tt>: suppression).</p> Full article ">
<p>Comparative analysis of IL8 and TIMP2 expression in normal skin, acne-affected, inflamed, and pigmented sites. IL8 and TIMP2 protein expression were quantified from (1) non-acneic skin, (2) normal skin, (3) sites of inflammation, and (4) sites of pigmentation in acneic skin by ELISA. * <span class="html-italic">p</span> < 0.05 versus control group; Student’s <span class="html-italic">t</span>-test. Data are expressed as the mean ± SEM.</p> Full article ">Figure 2
<p>IL8 and TIMP2 regulatory effects of chlorogenic acid and taurine in cultured HaCaT cells. The synergistic effect of chlorogenic acid and taurine on (<b>A</b>) IL8 inhibition, and (<b>B</b>) TIMP2 activation after 24 h of co-treatment with heat-killed <span class="html-italic">C. acnes</span>. * <span class="html-italic">p</span> < 0.05, ** <span class="html-italic">p</span> < 0.01, *** <span class="html-italic">p</span> < 0.001 relative to the control group; Student’s <span class="html-italic">t</span>-test. Data are expressed as mean ± SEM.</p> Full article ">Figure 3
<p>The synergistic effects of chlorogenic acid and taurine in wound closure and tight junction reinforcement in cultured HaCaT cells. (<b>A</b>) Synergistic wound-healing effect after 24 h treatment with chlorogenic acid and taurine treatment. (<b>B</b>) Upregulated claudin 1 expression after 24 h treatment was analyzed by immunostaining and fluorescence quantification. * <span class="html-italic">p</span> < 0.05, ** <span class="html-italic">p</span> < 0.01, *** <span class="html-italic">p</span> < 0.001 relative to the control group; Student’s <span class="html-italic">t</span>-test. Data are expressed as mean ± SEM.</p> Full article ">Figure 4
<p>Regulatory effects of chlorogenic acid and taurine on inflammatory cytokines and hydration markers. Treatment with chlorogenic acid and taurine for 24 h (<b>A</b>) decreased the mRNA and protein expression level of <span class="html-italic">IL1α</span>, <span class="html-italic">IL1β</span>, and <span class="html-italic">IL6</span>, and (<b>B</b>) increased mRNA and protein expression of <span class="html-italic">HAS3</span> in cultured HaCaT cells. * <span class="html-italic">p</span> < 0.05, ** <span class="html-italic">p</span> < 0.01 relative to the control group; Student’s <span class="html-italic">t</span>-test. Data are expressed as mean ± SEM.</p> Full article ">Figure 5
<p>Attenuation of irritated epidermis and enhancement of dermal density by treatment of chlorogenic acid and taurine. (<b>A</b>) The restorative effect of chlorogenic acid and taurine on an SLS-induced skin wound. ## <span class="html-italic">p</span> < 0.01 relative to treatment with SLS. * <span class="html-italic">p</span> < 0.05, ** <span class="html-italic">p</span> < 0.01 comparing the SLS applied and non-applied group. (<b>B</b>) Increment in epidermal and dermal density by long-term treatment of chlorogenic acid and taurine (yellow arrows: epidermis, red arrows: dermis).* <span class="html-italic">p</span> < 0.05, ** <span class="html-italic">p</span> < 0.01 versus before group; Student’s <span class="html-italic">t</span>-test. Data are expressed as mean ± SEM.</p> Full article ">Figure 6
<p>Summarized effects of chlorogenic acid and taurine in wound-healing effects (<tt>↑</tt>: activation, <tt>↓</tt>: suppression).</p> Full article ">
Open AccessArticle
Evaluation of Potential Furin Protease Inhibitory Properties of Pioglitazone, Rosiglitazone, and Pirfenidone: An In Silico Docking and Molecular Dynamics Simulation Approach
by
Ahtziri Socorro Carranza-Aranda, Carlos Daniel Diaz-Palomera, Eduardo Lepe-Reynoso, Anne Santerre, José Francisco Muñoz-Valle and Oliver Viera-Segura
Curr. Issues Mol. Biol. 2024, 46(8), 8665-8684; https://doi.org/10.3390/cimb46080511 - 8 Aug 2024
Abstract
Furin (Fur) is a member of the protease convertase family; its expression is crucial for cleaving and maturing many proteins. Fur also represents a therapeutic target in cancer, autoimmune diseases, and viral infections. Pioglitazone (PGZ) and rosiglitazone (RGZ) are thiazolidinediones prescribed to type
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Furin (Fur) is a member of the protease convertase family; its expression is crucial for cleaving and maturing many proteins. Fur also represents a therapeutic target in cancer, autoimmune diseases, and viral infections. Pioglitazone (PGZ) and rosiglitazone (RGZ) are thiazolidinediones prescribed to type 2 diabetes patients and are structurally similar to the known Fur inhibitors naphthofluorescein (NPF) and pirfenidone (PFD). Thus, this study used molecular docking and molecular dynamics to assess and compare the affinities and the molecular interactions of these four ligands with the Fur active site (FurAct) and the recently described Fur allosteric site (FurAll). The 7QXZ Fur structure was used for molecular dockings, and for the best pose complexes, molecular dynamics were run for 100 ns. The best affinities of the ligand/FurAct and ligand/FurAll complexes were with NPF, PGZ, and RGZ, while PFD presented the lowest affinity. Asp154 was the central residue involved in FurAct complex formation, while Glu488 and Asn310 were the central residues involved in FurAll complex formation. This study shows the potential of RGZ, PGZ, and PFD as Fur competitive (FurAct) and non-competitive (FurAll) inhibitors. Therefore, they are candidates for repurposing in response to future emerging diseases through the modulation of Fur activity.
Full article
(This article belongs to the Special Issue Synthesis and Theoretical Study of Bioactive Molecules)
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<p>Workflow diagram.</p> Full article ">Figure 2
<p>Representation of furin’s 3D general structure and domains (PDB ID: 7XQZ). Figure obtained with PyMOL v.2.5.4.</p> Full article ">Figure 3
<p>The 3D and 2D representations of the Fur active site (FurAct) and its molecular interactions with the potential ligands. (<b>A</b>,<b>B</b>) Overview of overlay complexes, (<b>C</b>) NPF, (<b>D</b>) PFD, (<b>E</b>) PGZ, and (<b>F</b>) RGZ. Figures obtained with the PyMOL v.2.5.4 and Discovery Studio v.21.1.0.20298 software.</p> Full article ">Figure 4
<p>The 3D and 2D representations of the Fur allosteric site (FurAll) and its molecular interactions with the potential ligands. (<b>A</b>,<b>B</b>) Overview of overlay complexes, (<b>C</b>) NPF, (<b>D</b>) PFD, (<b>E</b>) PGZ, and (<b>F</b>) RGZ. Figures obtained with the PyMOL v.2.5.4 and Discovery Studio v.21.1.0.20298 software.</p> Full article ">Figure 5
<p>RMSD of ligands/Fur complexes during MD simulation with (<b>A</b>) active site and (<b>B</b>) allosteric site of Fur. RMSD of complexes of NPF (naphtofluorescein), PFD (pirfenidone), PGZ (pioglitazone), and RGZ (rosiglitazone).</p> Full article ">Figure 6
<p>Rg of ligands/Fur complexes during MD simulation with (<b>A</b>) active site and (<b>B</b>) allosteric site of Fur. Rg of complexes of NPF (naphtofluorescein), PFD (pirfenidone), PGZ (pioglitazone), and RGZ (rosiglitazone).</p> Full article ">Figure 7
<p>Root mean square fluctuation (RMSF) values of ligand/Fur complexes within the Fur active site (FurAct; (<b>A</b>)) and Fur allosteric site (FurAll; (<b>B</b>)) during MD simulation for 100 ns. NPF: naphthofluorescein; PFD: pirferidone, PGZ: pioglitazona, RGZ: rosiglitazone. Figures obtained with Carma v.2.01 and Excel software v. 2406. Arrows indicate the critical residues on the Fur active site. The purple box indicates the catalytic domain. The blue box indicates the P domain.</p> Full article ">
<p>Workflow diagram.</p> Full article ">Figure 2
<p>Representation of furin’s 3D general structure and domains (PDB ID: 7XQZ). Figure obtained with PyMOL v.2.5.4.</p> Full article ">Figure 3
<p>The 3D and 2D representations of the Fur active site (FurAct) and its molecular interactions with the potential ligands. (<b>A</b>,<b>B</b>) Overview of overlay complexes, (<b>C</b>) NPF, (<b>D</b>) PFD, (<b>E</b>) PGZ, and (<b>F</b>) RGZ. Figures obtained with the PyMOL v.2.5.4 and Discovery Studio v.21.1.0.20298 software.</p> Full article ">Figure 4
<p>The 3D and 2D representations of the Fur allosteric site (FurAll) and its molecular interactions with the potential ligands. (<b>A</b>,<b>B</b>) Overview of overlay complexes, (<b>C</b>) NPF, (<b>D</b>) PFD, (<b>E</b>) PGZ, and (<b>F</b>) RGZ. Figures obtained with the PyMOL v.2.5.4 and Discovery Studio v.21.1.0.20298 software.</p> Full article ">Figure 5
<p>RMSD of ligands/Fur complexes during MD simulation with (<b>A</b>) active site and (<b>B</b>) allosteric site of Fur. RMSD of complexes of NPF (naphtofluorescein), PFD (pirfenidone), PGZ (pioglitazone), and RGZ (rosiglitazone).</p> Full article ">Figure 6
<p>Rg of ligands/Fur complexes during MD simulation with (<b>A</b>) active site and (<b>B</b>) allosteric site of Fur. Rg of complexes of NPF (naphtofluorescein), PFD (pirfenidone), PGZ (pioglitazone), and RGZ (rosiglitazone).</p> Full article ">Figure 7
<p>Root mean square fluctuation (RMSF) values of ligand/Fur complexes within the Fur active site (FurAct; (<b>A</b>)) and Fur allosteric site (FurAll; (<b>B</b>)) during MD simulation for 100 ns. NPF: naphthofluorescein; PFD: pirferidone, PGZ: pioglitazona, RGZ: rosiglitazone. Figures obtained with Carma v.2.01 and Excel software v. 2406. Arrows indicate the critical residues on the Fur active site. The purple box indicates the catalytic domain. The blue box indicates the P domain.</p> Full article ">
Open AccessBrief Report
TAAR8 Mediates Increased Migrasome Formation by Cadaverine in RPE Cells
by
Joon Bum Kim, Ji-Eun Bae, Na Yeon Park, Yong Hwan Kim, Seong Hyun Kim, Hyejin Hyung, Eunbyul Yeom, Dong Kyu Choi, Kwiwan Jeong and Dong-Hyung Cho
Curr. Issues Mol. Biol. 2024, 46(8), 8658-8664; https://doi.org/10.3390/cimb46080510 - 7 Aug 2024
Abstract
Migrasomes, the newly discovered cellular organelles that form large vesicle-like structures on the retraction fibers of migrating cells, are thought to be involved in communication between neighboring cells, cellular content transfer, unwanted material shedding, and information integration. Although their formation has been described
[...] Read more.
Migrasomes, the newly discovered cellular organelles that form large vesicle-like structures on the retraction fibers of migrating cells, are thought to be involved in communication between neighboring cells, cellular content transfer, unwanted material shedding, and information integration. Although their formation has been described previously, the molecular mechanisms of migrasome biogenesis are largely unknown. Here, we developed a cell line that overexpresses GFP-tetraspanin4, enabling observation of migrasomes. To identify compounds that regulate migrasome activity in retinal pigment epithelial (RPE) cells, we screened a fecal chemical library and identified cadaverine, a biogenic amine, as a potent migrasome formation inducer. Compared with normal migrating cells, those treated with cadaverine had significantly more migrasomes. Putrescine, another biogenic amine, also increased migrasome formation. Trace amine-associated receptor 8 (TAAR8) depletion inhibited migrasome increase in cadaverine-treated RPE cells, and cadaverine also inhibited protein kinase A phosphorylation. In RPE cells, cadaverine triggers migrasome formation via a TAAR8-mediated protein kinase A signaling pathway.
Full article
(This article belongs to the Section Biochemistry, Molecular and Cellular Biology)
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Figure 1
Figure 1
<p>Cadaverine and putrescine promote migrasome formation in RPE/GFP-TSPAN4 cells (<b>A</b>) A pie chart of the number of compounds in each phenotypic category. (<b>B</b>) The chemical structures of the diamine compounds, cadaverine and putrescine. (<b>C</b>) RPE/GFP-TSPAN4 cells were treated with cadaverine (50 μM) or putrescine (50 μM) for 24 h before being imaged under a fluorescence microscope. (<b>D</b>–<b>F</b>) Cadaverine- and putrescine-treated (24 h) RPE/GFP-TSPAN4 cells were counted migrasome numbers per cell (<b>D</b>), migrasome diameter, (<b>E</b>), and the number of migrasome-containing cells were counted (<b>F</b>). (<b>G</b>) Western blot analysis using the indicated antibodies. Measurements were made in about 200 cells per group. The red line represents the average value of the data. Data are presented as means ± SD. Statistical significance was assessed using one-way ANOVA, with ** and *** indicating <span class="html-italic">p</span> < 0.01 and <0.001, respectively. Scale bar: 20 μm.</p> Full article ">Figure 2
<p>TAAR8 knockdown inhibits migrasome formation in cadaverine-treated conditions (<b>A</b>,<b>B</b>). RPE/GFP-TSPAN4 cells were transiently transfected with scrambled siRNA (Sc, negative control) or anti-TAAR8 siRNA (siTAAR8), followed by treatment with cadaverine (50 μM) for 24 h and imaging under a fluorescence microscope (<b>A</b>). TAAR8 silencing was examined using western blot analysis with the indicated antibodies (<b>B</b>). (<b>C</b>–<b>E</b>) RPE/GFP-TSPAN4 cells were transiently transfected with scrambled siRNA (Sc, negative control) or anti-TAAR8 siRNA (siTAAR8) and then treated with cadaverine (50 μM) for 24 h. They were then fixed, and migrasome numbers per cell (<b>C</b>), migrasome diameter (<b>D</b>), and the number of migrasome-containing cells were then determined (<b>E</b>). Measurements were made in about 200 cells per group. The red line represents the average of the data. Data are presented as means ± SD. Statistical significance was assessed using one-way ANOVA, with ** and *** indicating <span class="html-italic">p</span> < 0.01 and <0.001, respectively. Scale bar: 10 μm.</p> Full article ">
<p>Cadaverine and putrescine promote migrasome formation in RPE/GFP-TSPAN4 cells (<b>A</b>) A pie chart of the number of compounds in each phenotypic category. (<b>B</b>) The chemical structures of the diamine compounds, cadaverine and putrescine. (<b>C</b>) RPE/GFP-TSPAN4 cells were treated with cadaverine (50 μM) or putrescine (50 μM) for 24 h before being imaged under a fluorescence microscope. (<b>D</b>–<b>F</b>) Cadaverine- and putrescine-treated (24 h) RPE/GFP-TSPAN4 cells were counted migrasome numbers per cell (<b>D</b>), migrasome diameter, (<b>E</b>), and the number of migrasome-containing cells were counted (<b>F</b>). (<b>G</b>) Western blot analysis using the indicated antibodies. Measurements were made in about 200 cells per group. The red line represents the average value of the data. Data are presented as means ± SD. Statistical significance was assessed using one-way ANOVA, with ** and *** indicating <span class="html-italic">p</span> < 0.01 and <0.001, respectively. Scale bar: 20 μm.</p> Full article ">Figure 2
<p>TAAR8 knockdown inhibits migrasome formation in cadaverine-treated conditions (<b>A</b>,<b>B</b>). RPE/GFP-TSPAN4 cells were transiently transfected with scrambled siRNA (Sc, negative control) or anti-TAAR8 siRNA (siTAAR8), followed by treatment with cadaverine (50 μM) for 24 h and imaging under a fluorescence microscope (<b>A</b>). TAAR8 silencing was examined using western blot analysis with the indicated antibodies (<b>B</b>). (<b>C</b>–<b>E</b>) RPE/GFP-TSPAN4 cells were transiently transfected with scrambled siRNA (Sc, negative control) or anti-TAAR8 siRNA (siTAAR8) and then treated with cadaverine (50 μM) for 24 h. They were then fixed, and migrasome numbers per cell (<b>C</b>), migrasome diameter (<b>D</b>), and the number of migrasome-containing cells were then determined (<b>E</b>). Measurements were made in about 200 cells per group. The red line represents the average of the data. Data are presented as means ± SD. Statistical significance was assessed using one-way ANOVA, with ** and *** indicating <span class="html-italic">p</span> < 0.01 and <0.001, respectively. Scale bar: 10 μm.</p> Full article ">
Open AccessCase Report
A New Case of Paediatric Systemic Lupus Erythematosus with Onset after SARS-CoV-2 and Epstein-Barr Infection—A Case Report and Literature Review
by
Carmen Loredana Petrea (Cliveți), Diana-Andreea Ciortea, Magdalena Miulescu, Iuliana-Laura Candussi, Sergiu Ioachim Chirila, Gabriela Isabela Verga (Răuță), Simona-Elena Bergheș, Mihai Ciprian Râșcu and Sorin Ion Berbece
Curr. Issues Mol. Biol. 2024, 46(8), 8642-8657; https://doi.org/10.3390/cimb46080509 - 7 Aug 2024
Abstract
Viral infections caused by exposure to viruses such as Epstein–Barr, cytomegalovirus, or Parvovirus B19 have always been considered predisposing environmental factors for the onset of autoimmune diseases. More recently, autoimmune mechanisms such as molecular mimicry, T-cell activation, transient immunosuppression and inflammation have also
[...] Read more.
Viral infections caused by exposure to viruses such as Epstein–Barr, cytomegalovirus, or Parvovirus B19 have always been considered predisposing environmental factors for the onset of autoimmune diseases. More recently, autoimmune mechanisms such as molecular mimicry, T-cell activation, transient immunosuppression and inflammation have also been observed in cases of SARS-CoV-2 infection. Several newly diagnosed autoimmune disorders have been reported post-COVID-19, such as COVID-19-associated multisystemic inflammatory syndrome in children (MIS-C), type 1 diabetes mellitus, systemic lupus erythematosus, or rheumatoid arthritis. In this article, we present a new case of paediatric systemic lupus erythematosus (SLE) with haematological (macrophage activation syndrome), renal (stage 2), cutaneous (urticarial vasculitis) and digestive involvement, onset three and a half months post-COVID-19. In the dynamics, de novo infection generated by Epstein–Barr exposure was associated. The diagnosis was confirmed based on EULAR/ACR 2019 criteria. The aim of the article is to present a possible correlation between SARS-CoV-2 and Epstein–Barr as extrinsic factors in triggering or activating paediatric systemic lupus erythematosus. Keywords: paediatric systemic lupus erythematosus; post-COVID-19; Epstein–Barr; SARS- CoV-2; case report; paediatric patient.
Full article
(This article belongs to the Collection Molecular Mechanisms in Human Diseases)
Open AccessReview
Keratins 6, 16, and 17 in Health and Disease: A Summary of Recent Findings
by
Daniil D. Romashin, Tatiana V. Tolstova, Alexandra M. Varshaver, Peter M. Kozhin, Alexander L. Rusanov and Natalia G. Luzgina
Curr. Issues Mol. Biol. 2024, 46(8), 8627-8641; https://doi.org/10.3390/cimb46080508 - 6 Aug 2024
Abstract
Keratins 6, 16, and 17 occupy unique positions within the keratin family. These proteins are not commonly found in the healthy, intact epidermis, but their expression increases in response to damage, inflammation, and hereditary skin conditions, as well as cancerous cell transformations and
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Keratins 6, 16, and 17 occupy unique positions within the keratin family. These proteins are not commonly found in the healthy, intact epidermis, but their expression increases in response to damage, inflammation, and hereditary skin conditions, as well as cancerous cell transformations and tumor growth. As a result, there is an active investigation into the potential use of these proteins as biomarkers for different pathologies. Recent studies have revealed the role of these keratins in regulating keratinocyte migration, proliferation, and growth, and more recently, their nuclear functions, including their role in maintaining nuclear structure and responding to DNA damage, have also been identified. This review aims to summarize the latest research on keratins 6, 16, and 17, their regulation in the epidermis, and their potential use as biomarkers in various skin conditions.
Full article
(This article belongs to the Special Issue Latest Review Papers in Molecular Biology 2024)
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![](https://pub.mdpi-res.com/cimb/cimb-46-00508/article_deploy/html/images/cimb-46-00508-g001-550.jpg?1722945658)
Figure 1
Figure 1
<p>Keratin 17 structure and assembly. (<b>A</b>) A schematic structure of keratin 17 showing non-helical domains at the N-terminus and C-terminus ends, with a central helical rod domain. K17’s structure consists of four alpha-helical domains (1A, 1B, 2A, and 2B), separated by three non-helical linkers (L1, L12, and L2). K17 also has two motifs, the helix initiation (him) and termination (hit) motifs, located at the ends of domains 1A and 2B, respectively. (<b>B</b>) A depiction of the alignment of the acidic type I keratins K17 and K16 along with the basic keratin K6, arranged in parallel to create a heterodimer. These heterodimers align in an antiparallel and staggered fashion to form a tetramer.</p> Full article ">Figure 2
<p>The cell functions of K6, K16, and K17. Damaged keratinocytes release various DAMPs, which induce the expression of K6/16/17 by activating the AP-1, NFkB, Nrf2, MAPK (ERK1/2 and p38) pathways. Altered expression of K17 promotes the secretion of Th1 cytokines (IFNγ, IL17A, and IL22) that maintain K6/16/17 expression through an autoimmune feedback loop. Keratin 17 regulates cell growth and proliferation by binding to the 14-3-3σ/AKT/mTOR pathway and STAT3 phosphorylation. When located in the nucleus, keratin 17 is involved in the DNA damage response by interacting with various DNA damage response proteins, including Aire, hnRNPK, H2AX, DNA-PKcs, 53BP1, and HMGN2. Keratin 16 modulates the secretion of DAMPs through the MAPK and EGFR signaling pathways and plays a role in maintaining the redox balance by interacting with the Nrf2 signaling pathway. Keratins K6 and K16 also play a role in regulating the morphology and functions of mitochondria. Keratin 6 is involved in regulating cell adhesion by directly interacting with myosin IIA and desmosomal proteins, which provide the mechanical properties necessary for wound healing.</p> Full article ">
<p>Keratin 17 structure and assembly. (<b>A</b>) A schematic structure of keratin 17 showing non-helical domains at the N-terminus and C-terminus ends, with a central helical rod domain. K17’s structure consists of four alpha-helical domains (1A, 1B, 2A, and 2B), separated by three non-helical linkers (L1, L12, and L2). K17 also has two motifs, the helix initiation (him) and termination (hit) motifs, located at the ends of domains 1A and 2B, respectively. (<b>B</b>) A depiction of the alignment of the acidic type I keratins K17 and K16 along with the basic keratin K6, arranged in parallel to create a heterodimer. These heterodimers align in an antiparallel and staggered fashion to form a tetramer.</p> Full article ">Figure 2
<p>The cell functions of K6, K16, and K17. Damaged keratinocytes release various DAMPs, which induce the expression of K6/16/17 by activating the AP-1, NFkB, Nrf2, MAPK (ERK1/2 and p38) pathways. Altered expression of K17 promotes the secretion of Th1 cytokines (IFNγ, IL17A, and IL22) that maintain K6/16/17 expression through an autoimmune feedback loop. Keratin 17 regulates cell growth and proliferation by binding to the 14-3-3σ/AKT/mTOR pathway and STAT3 phosphorylation. When located in the nucleus, keratin 17 is involved in the DNA damage response by interacting with various DNA damage response proteins, including Aire, hnRNPK, H2AX, DNA-PKcs, 53BP1, and HMGN2. Keratin 16 modulates the secretion of DAMPs through the MAPK and EGFR signaling pathways and plays a role in maintaining the redox balance by interacting with the Nrf2 signaling pathway. Keratins K6 and K16 also play a role in regulating the morphology and functions of mitochondria. Keratin 6 is involved in regulating cell adhesion by directly interacting with myosin IIA and desmosomal proteins, which provide the mechanical properties necessary for wound healing.</p> Full article ">
Open AccessArticle
The Combined Delivery of the Vegf, Ang, and Gdnf Genes Stimulates Angiogenesis and Improves Post-Ischemic Innervation and Regeneration in Skeletal Muscle
by
Igor Valerievich Samatoshenkov, Alexander Maazovich Aimaletdinov, Elena Yurievna Zakirova, Yuri Alexandrovich Chelyshev, Julia Maratovna Samatoshenkova, Marat Salimovich Kadyrov, Evgeny Alekseevich Kniazev, Bulat Ilgamovich Salakhov and Yana Olegovna Mukhamedshina
Curr. Issues Mol. Biol. 2024, 46(8), 8611-8626; https://doi.org/10.3390/cimb46080507 - 5 Aug 2024
Abstract
In this study, the effects of different combinations of the genes Vegf, Ang, and Gdnf injected both using direct virus-mediated injection (adenovirus, Ad5) and umbilical cord blood mononuclear cells (UCBCs) on the processes of stimulation of post-ischemic innervation, angiogenesis, and regeneration
[...] Read more.
In this study, the effects of different combinations of the genes Vegf, Ang, and Gdnf injected both using direct virus-mediated injection (adenovirus, Ad5) and umbilical cord blood mononuclear cells (UCBCs) on the processes of stimulation of post-ischemic innervation, angiogenesis, and regeneration in skeletal muscle were investigated in a rat hindlimb chronic ischemia model. It was shown that more pronounced stimulation of angiogenesis and restoration of post-ischemic innervation were achieved both in the early (28 days post-ischemia, dpi) and late (42 dpi) terms of the experiment in the calf muscle when UCBCs delivered the combination of Ad5-Vegf and Ad5-Ang compared to the direct injection of the same vector combination into the area of ischemia. At the same time, the inclusion of Ad5-Gdnf in the combination of Ad5-Vegf and Ad5-Ang directly injected or administered by UCBCs provided a significant increase in the number of centronuclear muscle fibers, indicating stimulation of post-ischemic reparative myogenesis. This study allowed us to determine the most effective gene combinations for angiogenesis and neurogenesis, which, in the future, may serve as the basis for the development of gene and gene cell products for the treatment of chronic lower limb ischemia.
Full article
(This article belongs to the Special Issue Molecular Mechanisms and Treatment of Ischemia–Reperfusion Injury)
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Graphical abstract
Graphical abstract
Full article ">Figure 1
<p>Schematic of the experiment. At 14 days after modeling ischemia, animals were injected with adenoviral vectors or UCBCs at 4 points in the distal part of the calf muscle. On 28 and 42 days after modeling ischemia (dpi), the animals were euthanized.</p> Full article ">Figure 2
<p>Distal part of the calf muscle in different terms after modeling ischemia. (<b>A</b>)—1 day after the creation of ischemia, ischemic damage to the muscle in the form of minor destruction of muscle fibers (arrows), cross section. (<b>B</b>)—14 days after the creation of ischemia, muscle fibers with disintegrated sarcoplasm disappear, transverse striation disappears, numerous CNMFs (arrows) appear, cross section. Hematoxylin and eosin staining. Light microscopy.</p> Full article ">Figure 3
<p>Distal part of the calf muscle at a distance of 500 μm from the injection area at 14 days after injection of Ad5-<span class="html-italic">Egfp</span> (<b>A</b>–<b>C</b>) or UCBC Ad5-<span class="html-italic">Egfp</span> (<b>D</b>) into the muscle. (<b>A</b>) Transverse slice; EGFP luminescence (green) contours the muscle fiber profile. (<b>B</b>,<b>C</b>) Lengthwise section; EGFP luminescence in the form of clusters distributed along the length of the fiber. (<b>D</b>)Lengthwise section; EGFP luminescence in cells in contact with muscle fibers. Nuclei stained with DAPI (blue). Confocal microscopy.</p> Full article ">Figure 4
<p>Number of CD31+ cells (<b>A</b>,<b>B</b>) and normal muscle fibers (<b>C</b>,<b>D</b>) at 28 and 42 dpi in the experimental groups. Groups with significant differences are combined by horizontal lines with serifs (<span class="html-italic">p</span> < 0.05).</p> Full article ">Figure 5
<p>Ratio of capillaries per normal muscle fiber (<b>A</b>,<b>B</b>) and number of centronuclear muscle fibers (<b>C</b>,<b>D</b>) at 28 and 42 dpi in experimental groups. Groups with significant differences are combined by horizontal lines with serifs (<span class="html-italic">p</span> < 0.05).</p> Full article ">Figure 6
<p>Number of S100b+ cells at 28 dpi (<b>A</b>) and 42 dpi (<b>B</b>) in the experimental groups. Groups with significant differences are combined by horizontal lines with serifs (<span class="html-italic">p</span> < 0.05). Immunohistochemical visualization of S100b+ cells in the following groups at 42 dpi: control (<b>C</b>), Ad5-<span class="html-italic">Vegf</span> (<b>D</b>), Ad5-<span class="html-italic">Vegf</span> + Ad5-<span class="html-italic">Ang</span> (<b>E</b>), Ad5-<span class="html-italic">Vegf</span> + Ad5-<span class="html-italic">Ang</span> + Ad5-<span class="html-italic">Gdnf</span> (<b>F</b>), UCBC Ad5-<span class="html-italic">Vegf</span> + Ad5-<span class="html-italic">Ang</span> + Ad5-<span class="html-italic">Gdnf</span> (<b>G</b>). Arrows indicate stained nerve fibers.</p> Full article ">Figure 7
<p>Number of nerve fibers (<b>A</b>) at 42 dpi in experimental groups. Groups with significant differences are combined by horizontal lines with serifs (<span class="html-italic">p</span> < 0.05). Immunohistochemical visualization of β3-tubulin+ fibers in Ad5- <span class="html-italic">Vegf</span> +Ad5-<span class="html-italic">Ang</span> (<b>B</b>), Ad5-<span class="html-italic">Vegf</span> +Ad5-<span class="html-italic">Ang</span> + Ad5-<span class="html-italic">Gdnf</span> (<b>C</b>), UCBC Ad5-<span class="html-italic">Vegf</span> + Ad5-<span class="html-italic">Ang</span> (<b>D</b>), UCBC Ad5-<span class="html-italic">Vegf</span> + Ad5-<span class="html-italic">Ang</span> + Ad5-<span class="html-italic">Ang</span> + Ad5-<span class="html-italic">Gdnf</span> (<b>E</b>) at 42 dpi in those groups. β3-tubulin+ fibers are indicated by arrows.</p> Full article ">
Full article ">Figure 1
<p>Schematic of the experiment. At 14 days after modeling ischemia, animals were injected with adenoviral vectors or UCBCs at 4 points in the distal part of the calf muscle. On 28 and 42 days after modeling ischemia (dpi), the animals were euthanized.</p> Full article ">Figure 2
<p>Distal part of the calf muscle in different terms after modeling ischemia. (<b>A</b>)—1 day after the creation of ischemia, ischemic damage to the muscle in the form of minor destruction of muscle fibers (arrows), cross section. (<b>B</b>)—14 days after the creation of ischemia, muscle fibers with disintegrated sarcoplasm disappear, transverse striation disappears, numerous CNMFs (arrows) appear, cross section. Hematoxylin and eosin staining. Light microscopy.</p> Full article ">Figure 3
<p>Distal part of the calf muscle at a distance of 500 μm from the injection area at 14 days after injection of Ad5-<span class="html-italic">Egfp</span> (<b>A</b>–<b>C</b>) or UCBC Ad5-<span class="html-italic">Egfp</span> (<b>D</b>) into the muscle. (<b>A</b>) Transverse slice; EGFP luminescence (green) contours the muscle fiber profile. (<b>B</b>,<b>C</b>) Lengthwise section; EGFP luminescence in the form of clusters distributed along the length of the fiber. (<b>D</b>)Lengthwise section; EGFP luminescence in cells in contact with muscle fibers. Nuclei stained with DAPI (blue). Confocal microscopy.</p> Full article ">Figure 4
<p>Number of CD31+ cells (<b>A</b>,<b>B</b>) and normal muscle fibers (<b>C</b>,<b>D</b>) at 28 and 42 dpi in the experimental groups. Groups with significant differences are combined by horizontal lines with serifs (<span class="html-italic">p</span> < 0.05).</p> Full article ">Figure 5
<p>Ratio of capillaries per normal muscle fiber (<b>A</b>,<b>B</b>) and number of centronuclear muscle fibers (<b>C</b>,<b>D</b>) at 28 and 42 dpi in experimental groups. Groups with significant differences are combined by horizontal lines with serifs (<span class="html-italic">p</span> < 0.05).</p> Full article ">Figure 6
<p>Number of S100b+ cells at 28 dpi (<b>A</b>) and 42 dpi (<b>B</b>) in the experimental groups. Groups with significant differences are combined by horizontal lines with serifs (<span class="html-italic">p</span> < 0.05). Immunohistochemical visualization of S100b+ cells in the following groups at 42 dpi: control (<b>C</b>), Ad5-<span class="html-italic">Vegf</span> (<b>D</b>), Ad5-<span class="html-italic">Vegf</span> + Ad5-<span class="html-italic">Ang</span> (<b>E</b>), Ad5-<span class="html-italic">Vegf</span> + Ad5-<span class="html-italic">Ang</span> + Ad5-<span class="html-italic">Gdnf</span> (<b>F</b>), UCBC Ad5-<span class="html-italic">Vegf</span> + Ad5-<span class="html-italic">Ang</span> + Ad5-<span class="html-italic">Gdnf</span> (<b>G</b>). Arrows indicate stained nerve fibers.</p> Full article ">Figure 7
<p>Number of nerve fibers (<b>A</b>) at 42 dpi in experimental groups. Groups with significant differences are combined by horizontal lines with serifs (<span class="html-italic">p</span> < 0.05). Immunohistochemical visualization of β3-tubulin+ fibers in Ad5- <span class="html-italic">Vegf</span> +Ad5-<span class="html-italic">Ang</span> (<b>B</b>), Ad5-<span class="html-italic">Vegf</span> +Ad5-<span class="html-italic">Ang</span> + Ad5-<span class="html-italic">Gdnf</span> (<b>C</b>), UCBC Ad5-<span class="html-italic">Vegf</span> + Ad5-<span class="html-italic">Ang</span> (<b>D</b>), UCBC Ad5-<span class="html-italic">Vegf</span> + Ad5-<span class="html-italic">Ang</span> + Ad5-<span class="html-italic">Ang</span> + Ad5-<span class="html-italic">Gdnf</span> (<b>E</b>) at 42 dpi in those groups. β3-tubulin+ fibers are indicated by arrows.</p> Full article ">
Open AccessArticle
A Bioinformatic Analysis Predicts That Cannabidiol Could Function as a Potential Inhibitor of the MAPK Pathway in Colorectal Cancer
by
Julianne du Plessis, Aurelie Deroubaix, Aadilah Omar and Clement Penny
Curr. Issues Mol. Biol. 2024, 46(8), 8600-8610; https://doi.org/10.3390/cimb46080506 - 5 Aug 2024
Abstract
Colorectal cancer (CRC), found in the intestinal tract, is initiated and progresses through various mechanisms, including the dysregulation of signaling pathways. Several signaling pathways, such as EGFR and MAPK, involved in cell proliferation, migration, and apoptosis, are often dysregulated in CRC. Although cannabidiol
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Colorectal cancer (CRC), found in the intestinal tract, is initiated and progresses through various mechanisms, including the dysregulation of signaling pathways. Several signaling pathways, such as EGFR and MAPK, involved in cell proliferation, migration, and apoptosis, are often dysregulated in CRC. Although cannabidiol (CBD) has previously induced apoptosis and cell cycle arrest in vitro in CRC cell lines, its effects on signaling pathways have not yet been determined. An in silico analysis was used here to assess partner proteins that can bind to CBD, and docking simulations were used to predict precisely where CBD would bind to these selected proteins. A survey of the current literature was used to hypothesize the effect of CBD binding on such proteins. The results predict that CBD could interact with EGFR, RAS/RAF isoforms, MEK1/2, and ERK1/2. The predicted CBD-induced inhibition might be due to CBD binding to the ATP binding site of the target proteins. This prevents the required phosphoryl transfer to activate substrate proteins and/or CBD binding to the DFG motif from taking place, thus reducing catalytic activity.
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(This article belongs to the Collection Bioinformatics Approaches to Biomedicine)
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<p>In silico analysis protocol. (<b>1</b>) The 3D structure of CBD was obtained from ChEBI as a .sdf file and uploaded to HT-Docking for binding prediction. (<b>2</b>) Pathway identification via Reactome and a literature review were conducted to identify suitable proteins involved in CRC. (<b>3</b>) Protein crystallography structure, in complex with a ligand, was obtained from Protein Data Bank, and then the ligand was removed using CCDC GOLD software. This new protein structure and CBD structure were uploaded to the CB dock 2 website to perform docking simulations. (<b>4</b>) The docked file was downloaded and opened using LigPlot to identify the amino acid residues involved in CBD binding to the protein. A literature review was then performed to predict the effect/s that CBD binding to these specific amino acids and binding sites could have on the target proteins’ functionality.</p> Full article ">Figure 2
<p>Binding site of CBD to various MAPK pathway proteins visualized with LigPlot. (<b>A</b>) BRAF, (<b>B</b>) EGFR, (<b>C</b>) KRAS, and (<b>D</b>) MEK1. Green—CBD; red—hydrogen bond; blue—hydrophobic interaction. The 3D conformation of CBD binding to various MAPK-pathway proteins visualized with PyMol. (<b>E</b>) BRAF, (<b>F</b>) EGFR, (<b>G</b>) KRAS, and (<b>H</b>) MEK1. Green—CBD; turquoise—helix; red—sheets.</p> Full article ">Figure 3
<p>Proposed schematic representation of the MAPK pathway with and without CBD. (<b>A</b>) In the absence of CBD, the MAPK pathway remains hyperactivated due to the unregulated activation of EGFR and MAPK pathway proteins. (<b>B</b>) In the presence of CBD, the proteins in the EGFR/MAPK pathway are inhibited through the abovementioned mechanisms. This will lead to the cascade-like prevention of target protein activation, resulting in a decrease in the activation and expression of proteins associated with cell migration, survival, and proliferation, among others.</p> Full article ">
<p>In silico analysis protocol. (<b>1</b>) The 3D structure of CBD was obtained from ChEBI as a .sdf file and uploaded to HT-Docking for binding prediction. (<b>2</b>) Pathway identification via Reactome and a literature review were conducted to identify suitable proteins involved in CRC. (<b>3</b>) Protein crystallography structure, in complex with a ligand, was obtained from Protein Data Bank, and then the ligand was removed using CCDC GOLD software. This new protein structure and CBD structure were uploaded to the CB dock 2 website to perform docking simulations. (<b>4</b>) The docked file was downloaded and opened using LigPlot to identify the amino acid residues involved in CBD binding to the protein. A literature review was then performed to predict the effect/s that CBD binding to these specific amino acids and binding sites could have on the target proteins’ functionality.</p> Full article ">Figure 2
<p>Binding site of CBD to various MAPK pathway proteins visualized with LigPlot. (<b>A</b>) BRAF, (<b>B</b>) EGFR, (<b>C</b>) KRAS, and (<b>D</b>) MEK1. Green—CBD; red—hydrogen bond; blue—hydrophobic interaction. The 3D conformation of CBD binding to various MAPK-pathway proteins visualized with PyMol. (<b>E</b>) BRAF, (<b>F</b>) EGFR, (<b>G</b>) KRAS, and (<b>H</b>) MEK1. Green—CBD; turquoise—helix; red—sheets.</p> Full article ">Figure 3
<p>Proposed schematic representation of the MAPK pathway with and without CBD. (<b>A</b>) In the absence of CBD, the MAPK pathway remains hyperactivated due to the unregulated activation of EGFR and MAPK pathway proteins. (<b>B</b>) In the presence of CBD, the proteins in the EGFR/MAPK pathway are inhibited through the abovementioned mechanisms. This will lead to the cascade-like prevention of target protein activation, resulting in a decrease in the activation and expression of proteins associated with cell migration, survival, and proliferation, among others.</p> Full article ">
Open AccessArticle
Dysregulation of Transposon Transcription Profiles in Cancer Cells Resembles That of Embryonic Stem Cells
by
Anna I. Solovyeva, Roman V. Afanasev, Marina A. Popova and Natella I. Enukashvily
Curr. Issues Mol. Biol. 2024, 46(8), 8576-8599; https://doi.org/10.3390/cimb46080505 - 5 Aug 2024
Abstract
Transposable elements (TEs) comprise a substantial portion of the mammalian genome, with potential implications for both embryonic development and cancer. This study aimed to characterize the expression profiles of TEs in embryonic stem cells (ESCs), cancer cell lines, tumor tissues, and the tumor
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Transposable elements (TEs) comprise a substantial portion of the mammalian genome, with potential implications for both embryonic development and cancer. This study aimed to characterize the expression profiles of TEs in embryonic stem cells (ESCs), cancer cell lines, tumor tissues, and the tumor microenvironment (TME). We observed similarities in TE expression profiles between cancer cells and ESCs, suggesting potential parallels in regulatory mechanisms. Notably, four TE RNAs (HERVH, LTR7, HERV-Fc1, HERV-Fc2) exhibited significant downregulation across cancer cell lines and tumor tissues compared to ESCs, highlighting potential roles in pluripotency regulation. The strong up-regulation of the latter two TEs (HERV-Fc1, HERV-Fc2) in ESCs has not been previously demonstrated and may be a first indication of their role in the regulation of pluripotency. Conversely, tandemly repeated sequences (MSR1, CER, ALR) showed up-regulation in cancer contexts. Moreover, a difference in TE expression was observed between the TME and the tumor bulk transcriptome, with distinct dysregulated TE profiles. Some TME-specific TEs were absent in normal tissues, predominantly belonging to LTR and L1 retrotransposon families. These findings not only shed light on the regulatory roles of TEs in both embryonic development and cancer but also suggest novel targets for anti-cancer therapy. Understanding the interplay between cancer cells and the TME at the TE level may pave the way for further research into therapeutic interventions.
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(This article belongs to the Special Issue The Significance of Transcription Factors, miRNAs, and lncRNAs in Anticancer Drug Development)
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<p>Pipelines of RNA-seq data analysis. (<b>a</b>) A scheme for bulk RNA-seq data processing, (<b>b</b>) a scheme for single-cell RNA-seq (scRNA-seq) data processing.</p> Full article ">Figure 2
<p>Venn diagrams illustrating comparisons of expressed TEs (<b>a</b>) between ESCs, fibroblasts, and cumulative tumor data, (<b>b</b>) ESCs, fibroblasts, and tumor tissues of different origins, and (<b>c</b>) ESCs, fibroblasts, and tumor cell lines originating from epithelial cancers (LUAD and NB). A549 and H1975—lung carcinoma cell lines, SK-N-SH—human neuroblastoma cell line, FBs—fibroblasts, NB—neuroblastoma, LUAD—lung adenocarcinoma, MM—multiple myeloma.</p> Full article ">Figure 3
<p>Venn diagrams illustrating the comparison of TE expression patterns between tumor tissues and corresponding cancer cell lines. (<b>a</b>) Neuroblastoma (NB) vs. SK-N-SH cell line, (<b>b</b>) lung adenocarcinoma (LUAD) vs. H1975 and A549 cell lines. A549 and H1975—LUAD cell lines, SK-N-SH—a human NB cell line.</p> Full article ">Figure 4
<p>Analysis of TEs differential expression. (<b>a</b>) The percentage of differentially expressed transposable elements (TEs) (DNA transposons, LINEs, SINEs, LTR/ERVs, and pseudogenes). (<b>b</b>) Heatmap based on log(TPM) of the top 50 differentially expressed repeats. The colors above the heatmap indicate the cell type, while the colors on the right of the heatmap indicate the type of repeat. Clusterization cladograms are also shown near the heatmap. LUAD—lung adenocarcinoma, MM—multiple myeloma, NB—neuroblastoma, ESCs—embryonic stem cells. TE IDs in (<b>b</b>) are shown as DfamID_TE name.</p> Full article ">Figure 5
<p>Volcano plots of differentially expressed TEs in normal fibroblasts, lung adenocarcinoma (LUAD), NB (neuroblastoma (NB), and LUAD cell line A549 vs. embryonic stem cells (ESCs) (<span class="html-italic">left column</span>) or in ESCs, LUAD, NB, A549 vs. fibroblasts (<span class="html-italic">right column</span>). <span class="html-italic">X</span>-axis—<span class="html-italic">b</span> or <span class="html-italic">beta</span>-value (log<sub>2</sub> fold changes between conditions) calculated by the Sleuth package. <span class="html-italic">Y</span> axis—lࢤog(q-value); the red dotted line corresponds to q-value < 0.05, the dots above the line are either up-regulated (b < 0) or downregulated (b > 0). The red dot in the LUAD vs fibroblasts plot corresponds to HERVH.</p> Full article ">Figure 6
<p>A Venn diagram illustration of TEs expressed in LUAD at the first level of cells clustering when cells are clusterized as stromal (fibroblasts and mesenchymal stromal cells or MSCs), endothelial, epithelial, and immune.</p> Full article ">
<p>Pipelines of RNA-seq data analysis. (<b>a</b>) A scheme for bulk RNA-seq data processing, (<b>b</b>) a scheme for single-cell RNA-seq (scRNA-seq) data processing.</p> Full article ">Figure 2
<p>Venn diagrams illustrating comparisons of expressed TEs (<b>a</b>) between ESCs, fibroblasts, and cumulative tumor data, (<b>b</b>) ESCs, fibroblasts, and tumor tissues of different origins, and (<b>c</b>) ESCs, fibroblasts, and tumor cell lines originating from epithelial cancers (LUAD and NB). A549 and H1975—lung carcinoma cell lines, SK-N-SH—human neuroblastoma cell line, FBs—fibroblasts, NB—neuroblastoma, LUAD—lung adenocarcinoma, MM—multiple myeloma.</p> Full article ">Figure 3
<p>Venn diagrams illustrating the comparison of TE expression patterns between tumor tissues and corresponding cancer cell lines. (<b>a</b>) Neuroblastoma (NB) vs. SK-N-SH cell line, (<b>b</b>) lung adenocarcinoma (LUAD) vs. H1975 and A549 cell lines. A549 and H1975—LUAD cell lines, SK-N-SH—a human NB cell line.</p> Full article ">Figure 4
<p>Analysis of TEs differential expression. (<b>a</b>) The percentage of differentially expressed transposable elements (TEs) (DNA transposons, LINEs, SINEs, LTR/ERVs, and pseudogenes). (<b>b</b>) Heatmap based on log(TPM) of the top 50 differentially expressed repeats. The colors above the heatmap indicate the cell type, while the colors on the right of the heatmap indicate the type of repeat. Clusterization cladograms are also shown near the heatmap. LUAD—lung adenocarcinoma, MM—multiple myeloma, NB—neuroblastoma, ESCs—embryonic stem cells. TE IDs in (<b>b</b>) are shown as DfamID_TE name.</p> Full article ">Figure 5
<p>Volcano plots of differentially expressed TEs in normal fibroblasts, lung adenocarcinoma (LUAD), NB (neuroblastoma (NB), and LUAD cell line A549 vs. embryonic stem cells (ESCs) (<span class="html-italic">left column</span>) or in ESCs, LUAD, NB, A549 vs. fibroblasts (<span class="html-italic">right column</span>). <span class="html-italic">X</span>-axis—<span class="html-italic">b</span> or <span class="html-italic">beta</span>-value (log<sub>2</sub> fold changes between conditions) calculated by the Sleuth package. <span class="html-italic">Y</span> axis—lࢤog(q-value); the red dotted line corresponds to q-value < 0.05, the dots above the line are either up-regulated (b < 0) or downregulated (b > 0). The red dot in the LUAD vs fibroblasts plot corresponds to HERVH.</p> Full article ">Figure 6
<p>A Venn diagram illustration of TEs expressed in LUAD at the first level of cells clustering when cells are clusterized as stromal (fibroblasts and mesenchymal stromal cells or MSCs), endothelial, epithelial, and immune.</p> Full article ">
Open AccessArticle
Protective Role of Astaxanthin in Regulating Lipopolysaccharide-Induced Inflammation and Apoptosis in Human Neutrophils
by
Seongheon Lee, Sung Kuk Son, Eunye Cho, Sungah Yoo, Eun-A Jang and Sang Hyun Kwak
Curr. Issues Mol. Biol. 2024, 46(8), 8567-8575; https://doi.org/10.3390/cimb46080504 - 5 Aug 2024
Abstract
Astaxanthin, a keto-carotenoid, is known to have potent antioxidant properties. This study aims to investigate the anti-inflammatory effect of astaxanthin and its mechanism in human neutrophils. The effects of astaxanthin on lipopolysaccharide (LPS)-stimulated human neutrophils were investigated in vitro. Neutrophils were isolated from
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Astaxanthin, a keto-carotenoid, is known to have potent antioxidant properties. This study aims to investigate the anti-inflammatory effect of astaxanthin and its mechanism in human neutrophils. The effects of astaxanthin on lipopolysaccharide (LPS)-stimulated human neutrophils were investigated in vitro. Neutrophils were isolated from healthy volunteers and stimulated with LPS in the presence and absence of astaxanthin. We assessed cytokine production, signaling pathway activation via mitogen-activated protein kinases (MAPKs) and nuclear factor kappa B (NF-κB), and apoptosis. Astaxanthin’s impact was evaluated at different concentrations, and both pretreatment and cotreatment protocols were tested. The results demonstrated that astaxanthin significantly reduced the production of pro-inflammatory cytokines TNF-α and IL-1β in LPS-stimulated neutrophils. It effectively inhibited the phosphorylation of ERK1/2 MAPK, without notably affecting p38 MAPK or NF-κB pathways. Furthermore, astaxanthin promoted apoptosis in neutrophils, counteracting the apoptosis-delaying effects of LPS. These effects were more pronounced with pretreatment. In conclusion, astaxanthin has protective effects on inflammatory responses in neutrophils by reducing cytokine production and enhancing apoptosis while selectively modulating intracellular signaling pathways. Astaxanthin demonstrates significant potential as a therapeutic agent in the management of severe inflammatory conditions.
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(This article belongs to the Section Molecular Pharmacology)
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<p>Experimental design used in the study. Astaxanthin (10, 50, 100 μM) was given before or together with LPS 100 ng/mL. Activation of intracellular signaling pathways (p38, ERK1/2, NF-κB) was analyzed by Western blot. Inflammatory cytokine levels were analyzed by ELISA. Quantification of neutrophil apoptosis was analyzed by flow cytometry. LPS, lipopolysaccharide; ERK1/2, extracellular signal-regulated kinase 1/2; NF-κB, nuclear factor kappa B; ELISA, enzyme-linked immunosorbent assay.</p> Full article ">Figure 2
<p>The effects of astaxanthin (ASTA) on inflammatory cytokine (TNF-α, IL-6, IL-1β) expression in human neutrophils stimulated by LPS. After being isolated from human blood, neutrophils were divided into 14 groups, as seen in experimental design (<a href="#cimb-46-00504-f001" class="html-fig">Figure 1</a>). Astaxanthin 10, 50, or 100 μM was added as pretreatment before LPS (pre-ASTA 10, 50, 100 + LPS), or together with LPS as cotreatment (ASTA 10, 50, 100 + LPS). Protein results were determined by ELISA. Data are shown as mean ± SD (n = 4 per group). † <span class="html-italic">p</span> < 0.05, vs. LPS. * <span class="html-italic">p</span> < 0.05, vs. control. TNF-α, tumor necrosis factor alpha; IL, interleukin; LPS, lipopolysaccharide; ELISA, enzyme-linked immunosorbent assay.</p> Full article ">Figure 3
<p>The effects of astaxanthin (ASTA) on mitogen-activated protein kinases (p38 and ERK1/2) and NF-κB activation in human neutrophils stimulated by LPS. Astaxanthin 50 or 100 μM was added as pretreatment before LPS (pre-ASTA 50, 100 + LPS), or together with LPS as cotreatment (ASTA 50, 100 + LPS). The phosphorylation (<span class="html-italic">p</span>) levels of p38, ERK1/2, and NF-κB were determined by Western blot analysis. Relative increase is the ratio of phosphorylated to β-actin. Data are shown as mean ± SD (n = 4 per group). † <span class="html-italic">p</span> < 0.05, vs. LPS. * <span class="html-italic">p</span> < 0.05, vs. control. ERK1/2, extracellular signal-regulated kinase 1/2; NF-κB, nuclear factor kappa B; LPS, lipopolysaccharide.</p> Full article ">Figure 4
<p>The effects of astaxanthin (ASTA) on apoptosis of human neutrophils stimulated by LPS. Astaxanthin 10, 50, or 100 μM was added as pretreatment before LPS (pre-ASTA 10, 50, 100 + LPS), or together with LPS as cotreatment (ASTA 10, 50, 100 + LPS). Contour diagram of FITC-Annexin V/PI flow cytometry of neutrophils for different groups. The lower right quadrants represent early apoptosis, FITC-Annexin V-positive and PI-negative. One representative experiment out of four is shown. The percentage of neutrophil apoptosis was represented for each group. Data are shown as mean ± SD (n = 4 per group). † <span class="html-italic">p</span> < 0.05, vs. LPS. * <span class="html-italic">p</span> < 0.05, vs. control. LPS, lipopolysaccharide; ERK1/2, extracellular signal-regulated kinase 1/2; NF-κB, nuclear factor kappa B; ELISA, enzyme-linked immunosorbent assay; FITC-Annexin V/PI, fluorescein isothiocyanate annexin V and propidium iodide.</p> Full article ">
<p>Experimental design used in the study. Astaxanthin (10, 50, 100 μM) was given before or together with LPS 100 ng/mL. Activation of intracellular signaling pathways (p38, ERK1/2, NF-κB) was analyzed by Western blot. Inflammatory cytokine levels were analyzed by ELISA. Quantification of neutrophil apoptosis was analyzed by flow cytometry. LPS, lipopolysaccharide; ERK1/2, extracellular signal-regulated kinase 1/2; NF-κB, nuclear factor kappa B; ELISA, enzyme-linked immunosorbent assay.</p> Full article ">Figure 2
<p>The effects of astaxanthin (ASTA) on inflammatory cytokine (TNF-α, IL-6, IL-1β) expression in human neutrophils stimulated by LPS. After being isolated from human blood, neutrophils were divided into 14 groups, as seen in experimental design (<a href="#cimb-46-00504-f001" class="html-fig">Figure 1</a>). Astaxanthin 10, 50, or 100 μM was added as pretreatment before LPS (pre-ASTA 10, 50, 100 + LPS), or together with LPS as cotreatment (ASTA 10, 50, 100 + LPS). Protein results were determined by ELISA. Data are shown as mean ± SD (n = 4 per group). † <span class="html-italic">p</span> < 0.05, vs. LPS. * <span class="html-italic">p</span> < 0.05, vs. control. TNF-α, tumor necrosis factor alpha; IL, interleukin; LPS, lipopolysaccharide; ELISA, enzyme-linked immunosorbent assay.</p> Full article ">Figure 3
<p>The effects of astaxanthin (ASTA) on mitogen-activated protein kinases (p38 and ERK1/2) and NF-κB activation in human neutrophils stimulated by LPS. Astaxanthin 50 or 100 μM was added as pretreatment before LPS (pre-ASTA 50, 100 + LPS), or together with LPS as cotreatment (ASTA 50, 100 + LPS). The phosphorylation (<span class="html-italic">p</span>) levels of p38, ERK1/2, and NF-κB were determined by Western blot analysis. Relative increase is the ratio of phosphorylated to β-actin. Data are shown as mean ± SD (n = 4 per group). † <span class="html-italic">p</span> < 0.05, vs. LPS. * <span class="html-italic">p</span> < 0.05, vs. control. ERK1/2, extracellular signal-regulated kinase 1/2; NF-κB, nuclear factor kappa B; LPS, lipopolysaccharide.</p> Full article ">Figure 4
<p>The effects of astaxanthin (ASTA) on apoptosis of human neutrophils stimulated by LPS. Astaxanthin 10, 50, or 100 μM was added as pretreatment before LPS (pre-ASTA 10, 50, 100 + LPS), or together with LPS as cotreatment (ASTA 10, 50, 100 + LPS). Contour diagram of FITC-Annexin V/PI flow cytometry of neutrophils for different groups. The lower right quadrants represent early apoptosis, FITC-Annexin V-positive and PI-negative. One representative experiment out of four is shown. The percentage of neutrophil apoptosis was represented for each group. Data are shown as mean ± SD (n = 4 per group). † <span class="html-italic">p</span> < 0.05, vs. LPS. * <span class="html-italic">p</span> < 0.05, vs. control. LPS, lipopolysaccharide; ERK1/2, extracellular signal-regulated kinase 1/2; NF-κB, nuclear factor kappa B; ELISA, enzyme-linked immunosorbent assay; FITC-Annexin V/PI, fluorescein isothiocyanate annexin V and propidium iodide.</p> Full article ">
Open AccessArticle
Genome-Wide Identification and Expression Analysis of the COL Gene Family in Hemerocallis citrina Baroni
by
Ziwei Zuo, Guangying Ma, Lupeng Xie, Xingda Yao, Shuxia Zhan and Yuan Zhou
Curr. Issues Mol. Biol. 2024, 46(8), 8550-8566; https://doi.org/10.3390/cimb46080503 - 5 Aug 2024
Abstract
Hemerocallis citrina Baroni (H. citrina) is an important specialty vegetable that is not only edible and medicinal but also has ornamental value. However, much remains unknown about the regulatory mechanisms associated with the growth, development, and flowering rhythm of this
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Hemerocallis citrina Baroni (H. citrina) is an important specialty vegetable that is not only edible and medicinal but also has ornamental value. However, much remains unknown about the regulatory mechanisms associated with the growth, development, and flowering rhythm of this plant. CO, as a core regulatory factor in the photoperiod pathway, coordinates light and circadian clock inputs to transmit flowering signals. We identified 18 COL genes (HcCOL1-HcCOL18) in the H. citrina cultivar ‘Mengzihua’ and studied their chromosomal distribution, phylogenetic relationships, gene and protein structures, collinearity, and expression levels in the floral organs at four developmental stages. The results indicate that these genes can be classified into three groups based on phylogenetic analysis. The major expansion of the HcCOL gene family occurred via segmental duplication, and the Ka/Ks ratio indicated that the COL genes of Arabidopsis thaliana, Oryza sativa, Phalaenopsis equestris, and H. citrina were under purifying selection. Many cis-elements, including light response elements, abiotic stress elements, and plant hormone-inducible elements, were distributed in the promoter sequences of the HcCOL genes. Expression analysis of HcCOL genes at four floral developmental stages revealed that most of the HcCOL genes were expressed in floral organs and might be involved in the growth, development, and senescence of the floral organs of H. citrina. This study lays a foundation for the further elucidation of the function of the HcCOL gene in H. citrina and provides a theoretical basis for the molecular design breeding of H. citrina.
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(This article belongs to the Section Molecular Plant Sciences)
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<p>The distribution of 18 COL genes on 11 chromosomes of <span class="html-italic">H. citrina</span>.</p> Full article ">Figure 2
<p>Structures of HcCOL genes and HcCOL proteins. (<b>A</b>) The structure of the HcCOL genes, with the blue box and yellow box representing the noncoding region (UTR) and coding sequence (CDS), respectively, and the black line representing the intron region. (<b>B</b>) The distribution of structural domains in the HcCOL proteins. The B-box, B-box SF, and CCT are represented by the cyan, pink, and green boxes, respectively.</p> Full article ">Figure 3
<p>Predicted three-dimensional structures of the B-box domains of the CO and HcCOL proteins. (<b>A</b>) Two B-box domains from AtCO. (<b>B</b>) HcCOL protein containing only one B-box domain. (<b>C</b>) HcCOL protein containing two B-box domains (showing some HcCOL proteins with the second B-box structural domain as B-box SF).</p> Full article ">Figure 4
<p>Sequence identities and similarities (%) between HcCOL proteins.</p> Full article ">Figure 5
<p>Comparison of the B-box domains of COL in <span class="html-italic">A</span>. <span class="html-italic">thaliana</span>, <span class="html-italic">O</span>. <span class="html-italic">sativa</span>, <span class="html-italic">P</span>. <span class="html-italic">equestris</span>, and <span class="html-italic">H</span>. <span class="html-italic">citrina</span>. The B-box1 and B-box2 domains are indicated by short lines in cyan and yellow, respectively, at the top of the sequences.</p> Full article ">Figure 6
<p>Comparison of the CCT domains of COL in <span class="html-italic">A</span>. <span class="html-italic">thaliana</span>, <span class="html-italic">O</span>. <span class="html-italic">sativa</span>, <span class="html-italic">P</span>. <span class="html-italic">equestris</span>, and <span class="html-italic">H</span>. <span class="html-italic">citrina</span>. The CCT domains are indicated by short lines in green at the top of the sequences.</p> Full article ">Figure 7
<p>Phylogenetic tree of COL proteins from four plant species. The neighbor-joining method was used to conduct the phylogenetic analysis of COL proteins from <span class="html-italic">A</span>. <span class="html-italic">thaliana</span> (COL), <span class="html-italic">O</span>. <span class="html-italic">sativa</span> (Os), <span class="html-italic">P</span>. <span class="html-italic">equestris</span> (Pe), and <span class="html-italic">H</span>. <span class="html-italic">citrina</span> (Hc).</p> Full article ">Figure 8
<p>Synteny analysis of the COL gene family. (<b>A</b>) Schematic representation of the interchromosomal relationships between the HcCOL genes in the <span class="html-italic">H</span>. <span class="html-italic">citrina</span> genome. The colored lines connect the collinear gene pairs, and the gray lines indicate the syntenic blocks in the <span class="html-italic">H</span>. <span class="html-italic">citrina</span> genome. (<b>B</b>) Synteny analysis of the COL genes between <span class="html-italic">H</span>. <span class="html-italic">citrina</span> and 3 representative species. Red lines highlight the colinear gene pair, while gray lines indicate the syntenic blocks within the <span class="html-italic">H</span>. <span class="html-italic">citrina</span> and other plant genomes.</p> Full article ">Figure 9
<p>Analysis of <span class="html-italic">cis</span>-elements within the promoters of HcCOL gene family members.</p> Full article ">Figure 10
<p>Expression levels of the HcCOL gene in F1 (young flower buds), F2 (flower buds), F3 (blooming flowers), and F4 (spent flowers). <span class="html-italic">AP4</span> was used as the internal reference gene. The values are the means ± SEMs of three biological replicates. The relative gene expression levels were calculated using the 2<sup>−ΔΔCt</sup> method. The letters above the histogram represent significant differences at <span class="html-italic">p</span> < 0.05.</p> Full article ">
<p>The distribution of 18 COL genes on 11 chromosomes of <span class="html-italic">H. citrina</span>.</p> Full article ">Figure 2
<p>Structures of HcCOL genes and HcCOL proteins. (<b>A</b>) The structure of the HcCOL genes, with the blue box and yellow box representing the noncoding region (UTR) and coding sequence (CDS), respectively, and the black line representing the intron region. (<b>B</b>) The distribution of structural domains in the HcCOL proteins. The B-box, B-box SF, and CCT are represented by the cyan, pink, and green boxes, respectively.</p> Full article ">Figure 3
<p>Predicted three-dimensional structures of the B-box domains of the CO and HcCOL proteins. (<b>A</b>) Two B-box domains from AtCO. (<b>B</b>) HcCOL protein containing only one B-box domain. (<b>C</b>) HcCOL protein containing two B-box domains (showing some HcCOL proteins with the second B-box structural domain as B-box SF).</p> Full article ">Figure 4
<p>Sequence identities and similarities (%) between HcCOL proteins.</p> Full article ">Figure 5
<p>Comparison of the B-box domains of COL in <span class="html-italic">A</span>. <span class="html-italic">thaliana</span>, <span class="html-italic">O</span>. <span class="html-italic">sativa</span>, <span class="html-italic">P</span>. <span class="html-italic">equestris</span>, and <span class="html-italic">H</span>. <span class="html-italic">citrina</span>. The B-box1 and B-box2 domains are indicated by short lines in cyan and yellow, respectively, at the top of the sequences.</p> Full article ">Figure 6
<p>Comparison of the CCT domains of COL in <span class="html-italic">A</span>. <span class="html-italic">thaliana</span>, <span class="html-italic">O</span>. <span class="html-italic">sativa</span>, <span class="html-italic">P</span>. <span class="html-italic">equestris</span>, and <span class="html-italic">H</span>. <span class="html-italic">citrina</span>. The CCT domains are indicated by short lines in green at the top of the sequences.</p> Full article ">Figure 7
<p>Phylogenetic tree of COL proteins from four plant species. The neighbor-joining method was used to conduct the phylogenetic analysis of COL proteins from <span class="html-italic">A</span>. <span class="html-italic">thaliana</span> (COL), <span class="html-italic">O</span>. <span class="html-italic">sativa</span> (Os), <span class="html-italic">P</span>. <span class="html-italic">equestris</span> (Pe), and <span class="html-italic">H</span>. <span class="html-italic">citrina</span> (Hc).</p> Full article ">Figure 8
<p>Synteny analysis of the COL gene family. (<b>A</b>) Schematic representation of the interchromosomal relationships between the HcCOL genes in the <span class="html-italic">H</span>. <span class="html-italic">citrina</span> genome. The colored lines connect the collinear gene pairs, and the gray lines indicate the syntenic blocks in the <span class="html-italic">H</span>. <span class="html-italic">citrina</span> genome. (<b>B</b>) Synteny analysis of the COL genes between <span class="html-italic">H</span>. <span class="html-italic">citrina</span> and 3 representative species. Red lines highlight the colinear gene pair, while gray lines indicate the syntenic blocks within the <span class="html-italic">H</span>. <span class="html-italic">citrina</span> and other plant genomes.</p> Full article ">Figure 9
<p>Analysis of <span class="html-italic">cis</span>-elements within the promoters of HcCOL gene family members.</p> Full article ">Figure 10
<p>Expression levels of the HcCOL gene in F1 (young flower buds), F2 (flower buds), F3 (blooming flowers), and F4 (spent flowers). <span class="html-italic">AP4</span> was used as the internal reference gene. The values are the means ± SEMs of three biological replicates. The relative gene expression levels were calculated using the 2<sup>−ΔΔCt</sup> method. The letters above the histogram represent significant differences at <span class="html-italic">p</span> < 0.05.</p> Full article ">
Open AccessArticle
Transgenic Drosophila melanogaster Carrying a Human Full-Length DISC1 Construct (UAS-hflDISC1) Showing Effects on Social Interaction Networks
by
Bobana Samardžija, Milan Petrović, Beti Zaharija, Marta Medija, Ana Meštrović, Nicholas J. Bradshaw, Ana Filošević Vujnović and Rozi Andretić Waldowski
Curr. Issues Mol. Biol. 2024, 46(8), 8526-8549; https://doi.org/10.3390/cimb46080502 - 3 Aug 2024
Abstract
Disrupted in Schizophrenia 1 (DISC1) is a scaffold protein implicated in major mental illnesses including schizophrenia, with a significant negative impact on social life. To investigate if DISC1 affects social interactions in Drosophila melanogaster, we created transgenic flies with second or third
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Disrupted in Schizophrenia 1 (DISC1) is a scaffold protein implicated in major mental illnesses including schizophrenia, with a significant negative impact on social life. To investigate if DISC1 affects social interactions in Drosophila melanogaster, we created transgenic flies with second or third chromosome insertions of the human full-length DISC1 (hflDISC1) gene fused to a UAS promotor (UAS-hflDISC1). Initial characterization of the insertion lines showed unexpected endogenous expression of the DISC1 protein that led to various behavioral and neurochemical phenotypes. Social interaction network (SIN) analysis showed altered social dynamics and organizational structures. This was in agreement with the altered levels of the locomotor activity of individual flies monitored for 24 h. Together with a decreased ability to climb vertical surfaces, the observed phenotypes indicate altered motor functions that could be due to a change in the function of the motor neurons and/or central brain. The changes in social behavior and motor function suggest that the inserted hflDISC1 gene influences nervous system functioning that parallels symptoms of DISC1-related mental diseases in humans. Furthermore, neurochemical analyses of transgenic lines revealed increased levels of hydrogen peroxide and decreased levels of glutathione, indicating an impact of DISC1 on the dynamics of redox regulation, similar to that reported in transgenic mammals. Future studies are needed to address the localization of DISC1 expression and to address how the redox parameter changes correlate with the observed behavioral changes.
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(This article belongs to the Special Issue The Regulation and Mechanisms of Genomics in Psychiatry)
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Figure 1
Figure 1
<p>DISC1 is a critical scaffold protein involved in multiple molecular mechanisms that affect neurodevelopment and synaptic function. Its dysregulation is linked to several symptoms of schizophrenia, including cognitive impairments, social withdrawal, psychosis, olfactory perception deficits, motor dysfunction, and disruptions in sleep and circadian patterns.</p> Full article ">Figure 2
<p>Centrality measures of social interaction networks in UAS-<span class="html-italic">hflDISC1</span> flies depend on site of insertion<b>.</b> All measurements were performed using n > 15 replicates of UAS<span class="html-italic">-hflDISC1-2nd</span> and UAS-<span class="html-italic">hflDISC1</span>-<span class="html-italic">3rd</span> and control <span class="html-italic">w<sup>1118</sup></span> male flies 3–5 days old. The parameters: global efficiency (<b>A</b>) and clustering coefficient (<b>B</b>,<b>C</b>), weighted either by the count (number) (<b>B</b>) or the duration (seconds) (<b>C</b>), were statistically analyzed using one-way ANOVA with Tukey’s multiple comparison post hoc test. Parameters betweenness centrality (<b>D</b>,<b>E</b>) and closeness centrality (<b>F</b>,<b>G</b>), weighted either by the count (number) (<b>D</b>,<b>F</b>) or the duration (duration) (<b>E</b>,<b>G</b>), were statistically analyzed using Kruskal–Wallis with Dunn’s test. <span class="html-italic">p</span> value style: APA < 0.05 (*), <0.01 (**), <0.001 (***).</p> Full article ">Figure 3
<p>The change in the locomotor activity in UAS-<span class="html-italic">hflDISC1</span> transgenic flies is age-dependent. (<b>A</b>,<b>B</b>), young flies 3–5 days old, and (<b>C</b>,<b>D</b>), flies aged 27–30 days. Activity was measured as the average value of the number of crossings of the middle of the tube in 1 min resolution from 16 individual flies per genotype. Data are then plotted as the average number of crossings of the midline of the tube averaged for 12 h (12 h light–12 h dark) for five days. Average day time activity ± SEM from 08:00 to 20:00 (<b>A</b>,<b>B</b>), and average activity during the night ± SEM from 20:00 to 08:00 (<b>C</b>,<b>D</b>). One-way ANOVA with Tukey’s multiple comparison post hoc test. <span class="html-italic">p</span> value style: APA < 0.05 (*) and <0.001 (***).</p> Full article ">Figure 4
<p>Decreased negative geotaxis in the UAS<span class="html-italic">-hflDISC1-3rd</span> transgenic flies. Test is performed on young flies 3–5 days old using driver lines UAS<span class="html-italic">-hflDISC1-2nd and</span> UAS<span class="html-italic">-hflDISC1</span>-3rd and <span class="html-italic">w<sup>1118</sup></span> control. A total of 10 flies were placed in a tube without food 30 min for adaptation. The vials were then struck three times onto a surface for all the flies to fall to the bottom of the vial, and then they were photographed 5 s later, to determine the percentage of flies that climbed over a height of 5 cm. Measurements were repeated five times for each group, with an interval of one minute between measurements Each genotype was tested with five groups of ten flies, with each group undergoing five trials. The results are presented as the mean value of the measurements in triplicate ± SEM (<span class="html-italic">n</span> = 50 per treatment, performed in 5 replicas). One-way ANOVA test with Bonferroni correction, <span class="html-italic">p</span> value style: APA < 0.05 (*).</p> Full article ">Figure 5
<p>Expression of DISC1 protein measured in the body (<b>A</b>) and head (<b>B</b>) homogenates depends on insertion place<b>.</b> Protein extracts were prepared form 3–5-day-old adult male flies in driver lines UAS-<span class="html-italic">hflDISC1-2nd and</span> UAS-<span class="html-italic">hflDISC1-3rd</span> and <span class="html-italic">w<sup>1118</sup></span> control. Body samples were prepared from 5 bodies without heads, and head samples were prepared from 20 heads. Data are presented as AVE ± SEM (<span class="html-italic">n</span> = 9). One-way ANOVA with Tukey’s multiple comparisons test. <span class="html-italic">p</span> value style: APA < 0.01 (**) and <0.001 (***).</p> Full article ">Figure 6
<p>Increased H<sub>2</sub>O<sub>2</sub> concentration in UAS-<span class="html-italic">hflDISC1</span> transgenic flies. Samples of 3–5-day-old UAS<span class="html-italic">-hflDISC1-2nd</span>, UAS<span class="html-italic">-hflDISC1-3rd</span>, and <span class="html-italic">w<sup>1118</sup></span> control flies were collected from (<b>A</b>) 5 adult male headless bodies and (<b>B</b>) 32 adult male heads to prepare homogenates using dihydroethidium (DHE). All measurements were performed in triplicate (<span class="html-italic">n</span> = 9). Data are presented as AVE ± SEM. One-way ANOVA with Tukey’s multiple comparison post hoc test. <span class="html-italic">p</span> value style: APA <0.05 (*) and <0.001 (***).</p> Full article ">Figure 7
<p>Decreased level of oxidized (GSH) but unchanged level of reduced glutathione (GSSG) in the UAS-<span class="html-italic">hflDISC1</span> headless bodies (<b>A</b>,<b>C</b>), and head homogenates (<b>B</b>,<b>D</b>). GSH (<b>A</b>,<b>B</b>) and GSSG (<b>C</b>,<b>D</b>) were measured using Ellman′s method reagent which reacts with the thiol group giving a product with the maximum absorbance at 415 nm. Using a calibration curve, GSH concentration was determined in homogenates of 5 adult headless male bodies or 32 adult male heads from 3–5-day-old adult UAS<span class="html-italic">-hflDISC1</span>-2nd, UAS<span class="html-italic">-hflDISC1-3rd</span>, and <span class="html-italic">w<sup>1118</sup></span> control flies. All measurements were performed in triplicate (<span class="html-italic">n</span> = 9). Data are presented as AVE ± SEM. One-way ANOVA with Tukey’s multiple comparison post hoc test. <span class="html-italic">p</span> value style: APA < 0.05 (*), < 0.01 (**), <0.001 (***).</p> Full article ">Figure A1
<p>The change in the locomotor activity in UAS-<span class="html-italic">hflDISC1</span> transgenic flies is age-dependent. (<b>A</b>), young flies 3–5 days old, and (<b>B</b>) flies aged 27–30 days. Activity was measured as the average value of the number of crossings of the middle of the tube in 1 min resolution from 16 flies per genotype. Data were then plotted as activity per one hour (average of 60 min interval from 16 flies). Line graphs are an average of 5 consecutive days of activity measurement in the DAMS system presented hour by hour.</p> Full article ">Figure A2
<p>The change in sleep amount in UAS-<span class="html-italic">hflDISC1</span> transgenic flies is age-dependent. (<b>A</b>–<b>C</b>) young flies 3–5 days old, and (<b>D</b>–<b>F</b>) flies aged 27–30 days. Sleep was measured as the average value of the number of 5-minute inactivity periods from 16 flies per genotype. Data were then plotted as sleep per one hour (average of 60 min interval from 16 flies). Line graphs are an average of 5 consecutive days of sleep presented hour by hour (<b>A</b>,<b>D</b>). The bar graph represents day time sleep as average ± SEM recorded from 08.00 in the morning to 20.00 in the evening (<b>B</b>,<b>E</b>), while night sleep was average ± SEM from 20.00 in the evening to 08.00 in the morning (<b>C</b>,<b>F</b>). One-way ANOVA with Tukey’s multiple comparison post hoc test. <span class="html-italic">p</span> value style: APA < 0.05 (*), <0.01 (**), <0.001 (***).</p> Full article ">Figure A2 Cont.
<p>The change in sleep amount in UAS-<span class="html-italic">hflDISC1</span> transgenic flies is age-dependent. (<b>A</b>–<b>C</b>) young flies 3–5 days old, and (<b>D</b>–<b>F</b>) flies aged 27–30 days. Sleep was measured as the average value of the number of 5-minute inactivity periods from 16 flies per genotype. Data were then plotted as sleep per one hour (average of 60 min interval from 16 flies). Line graphs are an average of 5 consecutive days of sleep presented hour by hour (<b>A</b>,<b>D</b>). The bar graph represents day time sleep as average ± SEM recorded from 08.00 in the morning to 20.00 in the evening (<b>B</b>,<b>E</b>), while night sleep was average ± SEM from 20.00 in the evening to 08.00 in the morning (<b>C</b>,<b>F</b>). One-way ANOVA with Tukey’s multiple comparison post hoc test. <span class="html-italic">p</span> value style: APA < 0.05 (*), <0.01 (**), <0.001 (***).</p> Full article ">Figure A3
<p>UAS<b>-</b><span class="html-italic">hflDISC1-2nd</span> transgenic flies have a decreased circadian period length. Activity was measured on flies 3–5 days old, under constant darkness for 5 days in row (<span class="html-italic">n</span> = 16 flies per genotype). The average value of the period length of individual flies was calculated from 5 days of activity recording using the ActoJ plugin in the ImageJ software. The bar graph presents the average ± SEM of period length. <span class="html-italic">p</span> value style: APA < 0.05 (*).</p> Full article ">Figure A4
<p>Expression of DISC1 protein measured in the body and head homogenates. Protein extracts were prepared form 3–5-day-old adult male flies in driver lines UAS<span class="html-italic">-hflDISC1-2nd and</span> UAS<span class="html-italic">-hflDISC1-3rd</span> and <span class="html-italic">w<sup>1118</sup></span> control. Body samples were prepared from 5 bodies without heads, and head samples were prepared from 20 heads.</p> Full article ">
<p>DISC1 is a critical scaffold protein involved in multiple molecular mechanisms that affect neurodevelopment and synaptic function. Its dysregulation is linked to several symptoms of schizophrenia, including cognitive impairments, social withdrawal, psychosis, olfactory perception deficits, motor dysfunction, and disruptions in sleep and circadian patterns.</p> Full article ">Figure 2
<p>Centrality measures of social interaction networks in UAS-<span class="html-italic">hflDISC1</span> flies depend on site of insertion<b>.</b> All measurements were performed using n > 15 replicates of UAS<span class="html-italic">-hflDISC1-2nd</span> and UAS-<span class="html-italic">hflDISC1</span>-<span class="html-italic">3rd</span> and control <span class="html-italic">w<sup>1118</sup></span> male flies 3–5 days old. The parameters: global efficiency (<b>A</b>) and clustering coefficient (<b>B</b>,<b>C</b>), weighted either by the count (number) (<b>B</b>) or the duration (seconds) (<b>C</b>), were statistically analyzed using one-way ANOVA with Tukey’s multiple comparison post hoc test. Parameters betweenness centrality (<b>D</b>,<b>E</b>) and closeness centrality (<b>F</b>,<b>G</b>), weighted either by the count (number) (<b>D</b>,<b>F</b>) or the duration (duration) (<b>E</b>,<b>G</b>), were statistically analyzed using Kruskal–Wallis with Dunn’s test. <span class="html-italic">p</span> value style: APA < 0.05 (*), <0.01 (**), <0.001 (***).</p> Full article ">Figure 3
<p>The change in the locomotor activity in UAS-<span class="html-italic">hflDISC1</span> transgenic flies is age-dependent. (<b>A</b>,<b>B</b>), young flies 3–5 days old, and (<b>C</b>,<b>D</b>), flies aged 27–30 days. Activity was measured as the average value of the number of crossings of the middle of the tube in 1 min resolution from 16 individual flies per genotype. Data are then plotted as the average number of crossings of the midline of the tube averaged for 12 h (12 h light–12 h dark) for five days. Average day time activity ± SEM from 08:00 to 20:00 (<b>A</b>,<b>B</b>), and average activity during the night ± SEM from 20:00 to 08:00 (<b>C</b>,<b>D</b>). One-way ANOVA with Tukey’s multiple comparison post hoc test. <span class="html-italic">p</span> value style: APA < 0.05 (*) and <0.001 (***).</p> Full article ">Figure 4
<p>Decreased negative geotaxis in the UAS<span class="html-italic">-hflDISC1-3rd</span> transgenic flies. Test is performed on young flies 3–5 days old using driver lines UAS<span class="html-italic">-hflDISC1-2nd and</span> UAS<span class="html-italic">-hflDISC1</span>-3rd and <span class="html-italic">w<sup>1118</sup></span> control. A total of 10 flies were placed in a tube without food 30 min for adaptation. The vials were then struck three times onto a surface for all the flies to fall to the bottom of the vial, and then they were photographed 5 s later, to determine the percentage of flies that climbed over a height of 5 cm. Measurements were repeated five times for each group, with an interval of one minute between measurements Each genotype was tested with five groups of ten flies, with each group undergoing five trials. The results are presented as the mean value of the measurements in triplicate ± SEM (<span class="html-italic">n</span> = 50 per treatment, performed in 5 replicas). One-way ANOVA test with Bonferroni correction, <span class="html-italic">p</span> value style: APA < 0.05 (*).</p> Full article ">Figure 5
<p>Expression of DISC1 protein measured in the body (<b>A</b>) and head (<b>B</b>) homogenates depends on insertion place<b>.</b> Protein extracts were prepared form 3–5-day-old adult male flies in driver lines UAS-<span class="html-italic">hflDISC1-2nd and</span> UAS-<span class="html-italic">hflDISC1-3rd</span> and <span class="html-italic">w<sup>1118</sup></span> control. Body samples were prepared from 5 bodies without heads, and head samples were prepared from 20 heads. Data are presented as AVE ± SEM (<span class="html-italic">n</span> = 9). One-way ANOVA with Tukey’s multiple comparisons test. <span class="html-italic">p</span> value style: APA < 0.01 (**) and <0.001 (***).</p> Full article ">Figure 6
<p>Increased H<sub>2</sub>O<sub>2</sub> concentration in UAS-<span class="html-italic">hflDISC1</span> transgenic flies. Samples of 3–5-day-old UAS<span class="html-italic">-hflDISC1-2nd</span>, UAS<span class="html-italic">-hflDISC1-3rd</span>, and <span class="html-italic">w<sup>1118</sup></span> control flies were collected from (<b>A</b>) 5 adult male headless bodies and (<b>B</b>) 32 adult male heads to prepare homogenates using dihydroethidium (DHE). All measurements were performed in triplicate (<span class="html-italic">n</span> = 9). Data are presented as AVE ± SEM. One-way ANOVA with Tukey’s multiple comparison post hoc test. <span class="html-italic">p</span> value style: APA <0.05 (*) and <0.001 (***).</p> Full article ">Figure 7
<p>Decreased level of oxidized (GSH) but unchanged level of reduced glutathione (GSSG) in the UAS-<span class="html-italic">hflDISC1</span> headless bodies (<b>A</b>,<b>C</b>), and head homogenates (<b>B</b>,<b>D</b>). GSH (<b>A</b>,<b>B</b>) and GSSG (<b>C</b>,<b>D</b>) were measured using Ellman′s method reagent which reacts with the thiol group giving a product with the maximum absorbance at 415 nm. Using a calibration curve, GSH concentration was determined in homogenates of 5 adult headless male bodies or 32 adult male heads from 3–5-day-old adult UAS<span class="html-italic">-hflDISC1</span>-2nd, UAS<span class="html-italic">-hflDISC1-3rd</span>, and <span class="html-italic">w<sup>1118</sup></span> control flies. All measurements were performed in triplicate (<span class="html-italic">n</span> = 9). Data are presented as AVE ± SEM. One-way ANOVA with Tukey’s multiple comparison post hoc test. <span class="html-italic">p</span> value style: APA < 0.05 (*), < 0.01 (**), <0.001 (***).</p> Full article ">Figure A1
<p>The change in the locomotor activity in UAS-<span class="html-italic">hflDISC1</span> transgenic flies is age-dependent. (<b>A</b>), young flies 3–5 days old, and (<b>B</b>) flies aged 27–30 days. Activity was measured as the average value of the number of crossings of the middle of the tube in 1 min resolution from 16 flies per genotype. Data were then plotted as activity per one hour (average of 60 min interval from 16 flies). Line graphs are an average of 5 consecutive days of activity measurement in the DAMS system presented hour by hour.</p> Full article ">Figure A2
<p>The change in sleep amount in UAS-<span class="html-italic">hflDISC1</span> transgenic flies is age-dependent. (<b>A</b>–<b>C</b>) young flies 3–5 days old, and (<b>D</b>–<b>F</b>) flies aged 27–30 days. Sleep was measured as the average value of the number of 5-minute inactivity periods from 16 flies per genotype. Data were then plotted as sleep per one hour (average of 60 min interval from 16 flies). Line graphs are an average of 5 consecutive days of sleep presented hour by hour (<b>A</b>,<b>D</b>). The bar graph represents day time sleep as average ± SEM recorded from 08.00 in the morning to 20.00 in the evening (<b>B</b>,<b>E</b>), while night sleep was average ± SEM from 20.00 in the evening to 08.00 in the morning (<b>C</b>,<b>F</b>). One-way ANOVA with Tukey’s multiple comparison post hoc test. <span class="html-italic">p</span> value style: APA < 0.05 (*), <0.01 (**), <0.001 (***).</p> Full article ">Figure A2 Cont.
<p>The change in sleep amount in UAS-<span class="html-italic">hflDISC1</span> transgenic flies is age-dependent. (<b>A</b>–<b>C</b>) young flies 3–5 days old, and (<b>D</b>–<b>F</b>) flies aged 27–30 days. Sleep was measured as the average value of the number of 5-minute inactivity periods from 16 flies per genotype. Data were then plotted as sleep per one hour (average of 60 min interval from 16 flies). Line graphs are an average of 5 consecutive days of sleep presented hour by hour (<b>A</b>,<b>D</b>). The bar graph represents day time sleep as average ± SEM recorded from 08.00 in the morning to 20.00 in the evening (<b>B</b>,<b>E</b>), while night sleep was average ± SEM from 20.00 in the evening to 08.00 in the morning (<b>C</b>,<b>F</b>). One-way ANOVA with Tukey’s multiple comparison post hoc test. <span class="html-italic">p</span> value style: APA < 0.05 (*), <0.01 (**), <0.001 (***).</p> Full article ">Figure A3
<p>UAS<b>-</b><span class="html-italic">hflDISC1-2nd</span> transgenic flies have a decreased circadian period length. Activity was measured on flies 3–5 days old, under constant darkness for 5 days in row (<span class="html-italic">n</span> = 16 flies per genotype). The average value of the period length of individual flies was calculated from 5 days of activity recording using the ActoJ plugin in the ImageJ software. The bar graph presents the average ± SEM of period length. <span class="html-italic">p</span> value style: APA < 0.05 (*).</p> Full article ">Figure A4
<p>Expression of DISC1 protein measured in the body and head homogenates. Protein extracts were prepared form 3–5-day-old adult male flies in driver lines UAS<span class="html-italic">-hflDISC1-2nd and</span> UAS<span class="html-italic">-hflDISC1-3rd</span> and <span class="html-italic">w<sup>1118</sup></span> control. Body samples were prepared from 5 bodies without heads, and head samples were prepared from 20 heads.</p> Full article ">
Open AccessArticle
Connecting the Dots: FGF21 as a Potential Link between Obesity and Cardiovascular Health in Acute Coronary Syndrome Patients
by
Cristina Elena Negroiu, Anca-Lelia Riza, Ioana Streață, Iulia Tudorașcu, Cristina Maria Beznă, Adrian Ionuț Ungureanu and Suzana Dănoiu
Curr. Issues Mol. Biol. 2024, 46(8), 8512-8525; https://doi.org/10.3390/cimb46080501 - 3 Aug 2024
Abstract
Fibroblast growth factor 21 (FGF21) is a hormone involved in regulating the metabolism, energy balance, and glucose homeostasis, with new studies demonstrating its beneficial effects on the heart. This study investigated the relationship between FGF21 levels and clinical, biochemical, and echocardiographic parameters in
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Fibroblast growth factor 21 (FGF21) is a hormone involved in regulating the metabolism, energy balance, and glucose homeostasis, with new studies demonstrating its beneficial effects on the heart. This study investigated the relationship between FGF21 levels and clinical, biochemical, and echocardiographic parameters in patients with acute coronary syndromes (ACSs). This study included 80 patients diagnosed with ACS between May and July 2023, categorized into four groups based on body mass index (BMI): Group 1 (BMI 18.5–24.9 kg/m2), Group 2 (BMI 25–29.9 kg/m2), Group 3 (BMI 30–34.9 kg/m2), and Group 4 (BMI ≥ 35 kg/m2). Serum FGF21 levels were measured by ELISA (Abclonal Catalog NO.: RK00084). Serum FGF21 levels were quantifiable in 55 samples (mean ± SD: 342.42 ± 430.17 pg/mL). Group-specific mean FGF21 levels were 238.98 pg/mL ± SD in Group 1 (n = 14), 296.78 pg/mL ± SD in Group 2 (n = 13), 373.77 pg/mL ± SD in Group 3 (n = 12), and 449.94 pg/mL ± SD in Group 4 (n = 16), with no statistically significant differences between groups (p = 0.47). Based on ACS diagnoses, mean FGF21 levels were 245.72 pg/mL for STEMI (n = 21), 257.89 pg/mL for NSTEMI (n = 9), and 456.28 pg/mL for unstable angina (n = 25), with no significant differences observed between these diagnostic categories. Significant correlations were identified between FGF21 levels and BMI, diastolic blood pressure, and serum chloride. Regression analyses revealed correlations with uric acid, chloride, and creatinine kinase MB. This study highlights the complex interplay between FGF21, BMI, and acute coronary syndromes. While no significant differences were found in FGF21 levels between the different BMI and ACS diagnostic groups, correlations with clinical and biochemical parameters suggest a multifaceted role of FGF21 in cardiovascular health. Further research with a larger sample size is warranted to elucidate these relationships.
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(This article belongs to the Section Molecular Medicine)
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Figure 1
<p>Distribution of Admission Diagnoses across BMI Groups in Study Patients.</p> Full article ">Figure 2
<p>Parameters with significant differences among the study groups: Group 1 includes 20 patients with a BMI between 18.5 and 24.9 kg/m<sup>2</sup>, (2) Group 2 includes 20 patients with a BMI between 25 and 29.9 kg/m<sup>2</sup>, (3) Group 3 includes 20 patients with a BMI between 30 and 34.9 kg/m<sup>2</sup>, and (4) Group 4 includes 20 patients with a BMI greater than 35 kg/m<sup>2</sup>. The panels show the comparison across groups for (<b>A</b>) weight, (<b>B</b>) waist circumference, (<b>C</b>) BMI, (<b>D</b>) interventricular septum thickness, (<b>E</b>) posterior wall thickness of the left ventricle, (<b>F</b>) inferior vena cava diameter, (<b>G</b>) aspartate aminotransferase levels, (<b>H</b>) triglycerides levels, (<b>I</b>) leukocytes and (<b>J</b>) erythrocyte sedimentation rate. Post hoc analysis was conducted to identify significant differences between the groups. Statistically significant differences (<span class="html-italic">p</span> < 0.05) are indicated. Error bars represent the standard deviation (SD).</p> Full article ">Figure 2 Cont.
<p>Parameters with significant differences among the study groups: Group 1 includes 20 patients with a BMI between 18.5 and 24.9 kg/m<sup>2</sup>, (2) Group 2 includes 20 patients with a BMI between 25 and 29.9 kg/m<sup>2</sup>, (3) Group 3 includes 20 patients with a BMI between 30 and 34.9 kg/m<sup>2</sup>, and (4) Group 4 includes 20 patients with a BMI greater than 35 kg/m<sup>2</sup>. The panels show the comparison across groups for (<b>A</b>) weight, (<b>B</b>) waist circumference, (<b>C</b>) BMI, (<b>D</b>) interventricular septum thickness, (<b>E</b>) posterior wall thickness of the left ventricle, (<b>F</b>) inferior vena cava diameter, (<b>G</b>) aspartate aminotransferase levels, (<b>H</b>) triglycerides levels, (<b>I</b>) leukocytes and (<b>J</b>) erythrocyte sedimentation rate. Post hoc analysis was conducted to identify significant differences between the groups. Statistically significant differences (<span class="html-italic">p</span> < 0.05) are indicated. Error bars represent the standard deviation (SD).</p> Full article ">Figure 3
<p>The FGF21 values in pg/mL in the conducted study.</p> Full article ">
<p>Distribution of Admission Diagnoses across BMI Groups in Study Patients.</p> Full article ">Figure 2
<p>Parameters with significant differences among the study groups: Group 1 includes 20 patients with a BMI between 18.5 and 24.9 kg/m<sup>2</sup>, (2) Group 2 includes 20 patients with a BMI between 25 and 29.9 kg/m<sup>2</sup>, (3) Group 3 includes 20 patients with a BMI between 30 and 34.9 kg/m<sup>2</sup>, and (4) Group 4 includes 20 patients with a BMI greater than 35 kg/m<sup>2</sup>. The panels show the comparison across groups for (<b>A</b>) weight, (<b>B</b>) waist circumference, (<b>C</b>) BMI, (<b>D</b>) interventricular septum thickness, (<b>E</b>) posterior wall thickness of the left ventricle, (<b>F</b>) inferior vena cava diameter, (<b>G</b>) aspartate aminotransferase levels, (<b>H</b>) triglycerides levels, (<b>I</b>) leukocytes and (<b>J</b>) erythrocyte sedimentation rate. Post hoc analysis was conducted to identify significant differences between the groups. Statistically significant differences (<span class="html-italic">p</span> < 0.05) are indicated. Error bars represent the standard deviation (SD).</p> Full article ">Figure 2 Cont.
<p>Parameters with significant differences among the study groups: Group 1 includes 20 patients with a BMI between 18.5 and 24.9 kg/m<sup>2</sup>, (2) Group 2 includes 20 patients with a BMI between 25 and 29.9 kg/m<sup>2</sup>, (3) Group 3 includes 20 patients with a BMI between 30 and 34.9 kg/m<sup>2</sup>, and (4) Group 4 includes 20 patients with a BMI greater than 35 kg/m<sup>2</sup>. The panels show the comparison across groups for (<b>A</b>) weight, (<b>B</b>) waist circumference, (<b>C</b>) BMI, (<b>D</b>) interventricular septum thickness, (<b>E</b>) posterior wall thickness of the left ventricle, (<b>F</b>) inferior vena cava diameter, (<b>G</b>) aspartate aminotransferase levels, (<b>H</b>) triglycerides levels, (<b>I</b>) leukocytes and (<b>J</b>) erythrocyte sedimentation rate. Post hoc analysis was conducted to identify significant differences between the groups. Statistically significant differences (<span class="html-italic">p</span> < 0.05) are indicated. Error bars represent the standard deviation (SD).</p> Full article ">Figure 3
<p>The FGF21 values in pg/mL in the conducted study.</p> Full article ">
Open AccessArticle
Diagnostic and Prognostic Role of Circulating microRNAs in Patients with Coronary Artery Disease—Impact on Left Ventricle and Arterial Function
by
Loredana Iacobescu, Andrea Olivia Ciobanu, Razvan Macarie, Mihaela Vadana, Letitia Ciortan, Monica Madalina Tucureanu, Elena Butoi, Maya Simionescu and Dragos Vinereanu
Curr. Issues Mol. Biol. 2024, 46(8), 8499-8511; https://doi.org/10.3390/cimb46080500 - 3 Aug 2024
Abstract
Recent studies reported that circulating microRNAs (miRNAs) can target different metalloproteases (MMPs) involved in matrix remodeling and plaque vulnerability. Consequently, they might have a role in the diagnosis and prognosis of coronary artery disease. To quantify circulating miRNAs (miRNA126, miRNA146, and miRNA21) suggested
[...] Read more.
Recent studies reported that circulating microRNAs (miRNAs) can target different metalloproteases (MMPs) involved in matrix remodeling and plaque vulnerability. Consequently, they might have a role in the diagnosis and prognosis of coronary artery disease. To quantify circulating miRNAs (miRNA126, miRNA146, and miRNA21) suggested to have possible cardiovascular implications, as well as levels of MMP-1 and MMP-9, and to determine their association with left ventricular (LV) function and with arterial function, in patients with either ST-segment elevation acute myocardial infarction (STEMI) or stable ischemic heart disease (SIHD). A total of 90 patients with coronary artery disease (61% men, 58 ± 12 years), including 60 patients with STEMI and 30 patients with SIHD, were assessed within 24 h of admission, by measuring serum microRNAs, and serum MMP-1 and MMP-9. LV function was assessed by measuring ejection fraction (EF) by 2D and 3D echocardiography, and global longitudinal strain (GLS) by speckle tracking. Arterial function was assessed by echo tracking, CAVI, and peripheral Doppler. Circulating levels of miRNA146, miRNA21, and MMP1 were significantly increased in patients with STEMI vs. SIHD (p = 0.0001, p = 0.0001, p = 0.04, respectively). MiRNA126 negatively correlated with LVEF (r = −0.33, p = 0.01) and LV deformation parameters (r = −0.31, p = 0.03) in patients with STEMI and negatively correlated with ABI parameters (r = −0.39, p = 0.03, r = −0.40, p = 0.03, respectively) in patients with SIHD. MiRNA146 did not have any significant correlations, while higher values of miRNA21 were associated with lower values of GLS in STEMI patients and with higher values of GLS in SIHD patients. Both MMP1 and MMP9 correlated negatively with LVEF (r = −0.27, p = 0.04, r = −0.40, p = 0.001, respectively) and GLS in patients with STEMI, and positively with arterial stiffness in patients with SIHD (r = 0.40 and r = 0.32, respectively; both p < 0.05). MiRNA126, miRNA21, and both MMP1 and MMP9 are associated with LV and arterial function parameters in patients with acute coronary syndrome. Meanwhile, they inversely correlate with arterial function in patients with chronic atherosclerotic disease. However, further studies are needed to establish whether these novel biomarkers have diagnosis and prognosis significance.
Full article
(This article belongs to the Section Biochemistry, Molecular and Cellular Biology)
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![](https://pub.mdpi-res.com/cimb/cimb-46-00500/article_deploy/html/images/cimb-46-00500-g001-550.jpg?1722924512)
Figure 1
Figure 1
<p>Circulating levels of miRNAs (miRNA146—1<b>a</b>, miRNA21—1<b>b</b>, miRNA126—1<b>e</b>) and MMPs (MMP1—1<b>c</b>, MMP9—1<b>d</b>) in patients with STEMI (Group 1) vs. SIHD (Group 2).</p> Full article ">Figure 2
<p>Pearson’s correlations between miRNA126 and 2D LVEF (<b>a</b>), 3D CS (<b>b</b>), LCAVI (<b>c</b>), and RCAVI (<b>d</b>) in patients with STEMI. LVEF = left ventricular ejection fraction; CS = circumferential strain; R/L = CAVI right/left cardio-ankle vascular index.</p> Full article ">Figure 3
<p>Pearson’s correlations between miRNA126 and LABI (<b>a</b>) and RABI (<b>b</b>) in patients with SIHD. LABI = left ankle-brachial index; RABI = right ankle-brachial index.</p> Full article ">Figure 4
<p>Pearson’s correlations between miRNA21 and 3D LS in patients with SIHD (<b>a</b>), and 3D LS in patients with STEMI (<b>b</b>). LS = longitudinal strain.</p> Full article ">Figure 5
<p>Pearson’s negative correlation between MMP1 (<b>a</b>) and MMP9 (<b>b</b>) and 2D LVEF in patients with STEMI. LVEF = left ventricular ejection fraction.</p> Full article ">Figure 6
<p>Positive significant correlation between MMP9 (<b>a</b>) and miRNA21 (<b>b</b>) and troponin in the first 24 h of admission, in patients with STEMI.</p> Full article ">
<p>Circulating levels of miRNAs (miRNA146—1<b>a</b>, miRNA21—1<b>b</b>, miRNA126—1<b>e</b>) and MMPs (MMP1—1<b>c</b>, MMP9—1<b>d</b>) in patients with STEMI (Group 1) vs. SIHD (Group 2).</p> Full article ">Figure 2
<p>Pearson’s correlations between miRNA126 and 2D LVEF (<b>a</b>), 3D CS (<b>b</b>), LCAVI (<b>c</b>), and RCAVI (<b>d</b>) in patients with STEMI. LVEF = left ventricular ejection fraction; CS = circumferential strain; R/L = CAVI right/left cardio-ankle vascular index.</p> Full article ">Figure 3
<p>Pearson’s correlations between miRNA126 and LABI (<b>a</b>) and RABI (<b>b</b>) in patients with SIHD. LABI = left ankle-brachial index; RABI = right ankle-brachial index.</p> Full article ">Figure 4
<p>Pearson’s correlations between miRNA21 and 3D LS in patients with SIHD (<b>a</b>), and 3D LS in patients with STEMI (<b>b</b>). LS = longitudinal strain.</p> Full article ">Figure 5
<p>Pearson’s negative correlation between MMP1 (<b>a</b>) and MMP9 (<b>b</b>) and 2D LVEF in patients with STEMI. LVEF = left ventricular ejection fraction.</p> Full article ">Figure 6
<p>Positive significant correlation between MMP9 (<b>a</b>) and miRNA21 (<b>b</b>) and troponin in the first 24 h of admission, in patients with STEMI.</p> Full article ">
Open AccessReview
Therapeutic Application and Structural Features of Adeno-Associated Virus Vector
by
Yasunari Matsuzaka and Ryu Yashiro
Curr. Issues Mol. Biol. 2024, 46(8), 8464-8498; https://doi.org/10.3390/cimb46080499 - 2 Aug 2024
Abstract
Adeno-associated virus (AAV) is characterized by non-pathogenicity, long-term infection, and broad tropism and is actively developed as a vector virus for gene therapy products. AAV is classified into more than 100 serotypes based on differences in the amino acid sequence of the capsid
[...] Read more.
Adeno-associated virus (AAV) is characterized by non-pathogenicity, long-term infection, and broad tropism and is actively developed as a vector virus for gene therapy products. AAV is classified into more than 100 serotypes based on differences in the amino acid sequence of the capsid protein. Endocytosis involves the uptake of viral particles by AAV and accessory receptors during AAV infection. After entry into the cell, they are transported to the nucleus through the nuclear pore complex. AAVs mainly use proteoglycans as receptors to enter cells, but the types of sugar chains in proteoglycans that have binding ability are different. Therefore, it is necessary to properly evaluate the primary structure of receptor proteins, such as amino acid sequences and post-translational modifications, including glycosylation, and the higher-order structure of proteins, such as the folding of the entire capsid structure and the three-dimensional (3D) structure of functional domains, to ensure the efficacy and safety of biopharmaceuticals. To further enhance safety, it is necessary to further improve the efficiency of gene transfer into target cells, reduce the amount of vector administered, and prevent infection of non-target cells.
Full article
(This article belongs to the Special Issue Mesenchymal-Stem-Cell-Based Therapeutic Strategies via Extracellular Vesicles)
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Figure 1
Figure 1
<p>Structure of the wild-type AAV genome. Rep78 and Rep68 are expressed from the p5 promoter and Rep52 and Rep40 from the p19 promoter. VP1, 2, 3 and the assembly-activating protein (AAP) are translated from the p40 transcript encoded by the cap gene.</p> Full article ">Figure 2
<p><b>(Upper)</b> Amino acid sequence in VP1 and VP2 of AAV type 1 to type 12. (<b>Bottom</b>) Amino acid identity of VP1 and VP2 of AAV type 1 to type 12. Yellows highlight the conserved amino acid motif. BR3 domain is indicated by green.</p> Full article ">Figure 2 Cont.
<p><b>(Upper)</b> Amino acid sequence in VP1 and VP2 of AAV type 1 to type 12. (<b>Bottom</b>) Amino acid identity of VP1 and VP2 of AAV type 1 to type 12. Yellows highlight the conserved amino acid motif. BR3 domain is indicated by green.</p> Full article ">Figure 3
<p>AAV2 structures at a 9.7-Å resolution. Example capsid surface regions corresponding to VR-I and VR-IV are indicated by arrows in panels [<a href="#B45-cimb-46-00499" class="html-bibr">45</a>].</p> Full article ">Figure 4
<p>Transduction model of by AAV vectors via binding AAV to cell surface receptor. AAV was internalized into cytoplasm of cell by endosomal trafficking via interaction with AAV receptor (AAVR). The internalized AAVs entry into nucleus through endosomal escape, and then the AAVs within the nucleus release viral single-stranded DNA via uncoating, which forms nucleoprotein filament complex due to transcription.</p> Full article ">Figure 5
<p>Allele frequency of HLA class II genes [<a href="#B126-cimb-46-00499" class="html-bibr">126</a>,<a href="#B131-cimb-46-00499" class="html-bibr">131</a>,<a href="#B132-cimb-46-00499" class="html-bibr">132</a>].</p> Full article ">Figure 6
<p>Construction of AAV variant library.</p> Full article ">
<p>Structure of the wild-type AAV genome. Rep78 and Rep68 are expressed from the p5 promoter and Rep52 and Rep40 from the p19 promoter. VP1, 2, 3 and the assembly-activating protein (AAP) are translated from the p40 transcript encoded by the cap gene.</p> Full article ">Figure 2
<p><b>(Upper)</b> Amino acid sequence in VP1 and VP2 of AAV type 1 to type 12. (<b>Bottom</b>) Amino acid identity of VP1 and VP2 of AAV type 1 to type 12. Yellows highlight the conserved amino acid motif. BR3 domain is indicated by green.</p> Full article ">Figure 2 Cont.
<p><b>(Upper)</b> Amino acid sequence in VP1 and VP2 of AAV type 1 to type 12. (<b>Bottom</b>) Amino acid identity of VP1 and VP2 of AAV type 1 to type 12. Yellows highlight the conserved amino acid motif. BR3 domain is indicated by green.</p> Full article ">Figure 3
<p>AAV2 structures at a 9.7-Å resolution. Example capsid surface regions corresponding to VR-I and VR-IV are indicated by arrows in panels [<a href="#B45-cimb-46-00499" class="html-bibr">45</a>].</p> Full article ">Figure 4
<p>Transduction model of by AAV vectors via binding AAV to cell surface receptor. AAV was internalized into cytoplasm of cell by endosomal trafficking via interaction with AAV receptor (AAVR). The internalized AAVs entry into nucleus through endosomal escape, and then the AAVs within the nucleus release viral single-stranded DNA via uncoating, which forms nucleoprotein filament complex due to transcription.</p> Full article ">Figure 5
<p>Allele frequency of HLA class II genes [<a href="#B126-cimb-46-00499" class="html-bibr">126</a>,<a href="#B131-cimb-46-00499" class="html-bibr">131</a>,<a href="#B132-cimb-46-00499" class="html-bibr">132</a>].</p> Full article ">Figure 6
<p>Construction of AAV variant library.</p> Full article ">
Open AccessReview
Is Copper Still Safe for Us? What Do We Know and What Are the Latest Literature Statements?
by
Angelika Edyta Charkiewicz
Curr. Issues Mol. Biol. 2024, 46(8), 8441-8463; https://doi.org/10.3390/cimb46080498 - 2 Aug 2024
Abstract
Copper (Cu) is a precious metal and one of the three most abundant trace elements in the body (50–120 mg). It is involved in a large number of cellular mechanisms and pathways and is an essential cofactor in the function of cellular enzymes.
[...] Read more.
Copper (Cu) is a precious metal and one of the three most abundant trace elements in the body (50–120 mg). It is involved in a large number of cellular mechanisms and pathways and is an essential cofactor in the function of cellular enzymes. Both its excess and deficiency may be harmful for many diseases. Even small changes in Cu concentration may be associated with significant toxicity. Consequently, it can be damaging to any organ or tissue in our body, beginning with harmful effects already at the molecular level and then affecting the degradation of individual tissues/organs and the slow development of many diseases, such as those of the immunological system, skeletal system, circulatory system, nervous system, digestive system, respiratory system, reproductive system, and skin. The main purpose of this article is to review the literature with regard to both the healthiness and toxicity of copper to the human body. A secondary objective is to show its widespread use and sources, including in food and common materials in contact with humans. Its biological half-life from diet is estimated to range from 13 to 33 days. The retention or bioavailability of copper from the diet is influenced by several factors, such as age, amount and form of copper in the diet, lifestyle, and genetic background. The upper limit of normal in serum in healthy adults is approximately 1.5 mg Cu/L, while the safe upper limit of average intake is set at 10–12 mg/day, the reference limit at 0.9 mg/day, and the minimum limit at 0.6–0.7 mg/day. Cu is essential, and in the optimal dose, it provides antioxidant defense, while its deficiency reduces the body’s ability to cope with oxidative stress. The development of civilization and the constant, widespread use of Cu in all electrical devices will not be stopped, but the health of people directly related to its extraction, production, or distribution can be controlled, and the inhabitants of nearby towns can be protected. It is extremely difficult to assess the effects of copper on the human body because of its ubiquity and the increasing reports in the literature about its effects, including copper nanoparticles.
Full article
(This article belongs to the Special Issue Latest Review Papers in Molecular Biology 2024)
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Open AccessArticle
Using Precision Medicine to Disentangle Genotype–Phenotype Relationships in Twins with Rett Syndrome: A Case Report
by
Jatinder Singh, Georgina Wilkins, Ella Goodman-Vincent, Samiya Chishti, Ruben Bonilla Guerrero, Federico Fiori, Shashidhar Ameenpur, Leighton McFadden, Zvi Zahavi and Paramala Santosh
Curr. Issues Mol. Biol. 2024, 46(8), 8424-8440; https://doi.org/10.3390/cimb46080497 - 2 Aug 2024
Abstract
Rett syndrome (RTT) is a paediatric neurodevelopmental disorder spanning four developmental stages. This multi-system disorder offers a unique window to explore genotype–phenotype relationships in a disease model. However, genetic prognosticators of RTT have limited clinical value due to the disorder’s heterogeneity on multiple
[...] Read more.
Rett syndrome (RTT) is a paediatric neurodevelopmental disorder spanning four developmental stages. This multi-system disorder offers a unique window to explore genotype–phenotype relationships in a disease model. However, genetic prognosticators of RTT have limited clinical value due to the disorder’s heterogeneity on multiple levels. This case report used a precision medicine approach to better understand the clinical phenotype of RTT twins with an identical pathogenic MECP2 mutation and discordant neurodevelopmental profiles. Targeted genotyping, objective physiological monitoring of heart rate variability (HRV) parameters, and clinical severity were assessed in a RTT twin pair (5 years 7 months old) with an identical pathogenic MECP2 mutation. Longitudinal assessment of autonomic HRV parameters was conducted using the Empatica E4 wristband device, and clinical severity was assessed using the RTT-anchored Clinical Global Impression Scale (RTT-CGI) and the Multi-System Profile of Symptoms Scale (MPSS). Genotype data revealed impaired BDNF function for twin A when compared to twin B. Twin A also had poorer autonomic health than twin B, as indicated by lower autonomic metrics (autonomic inflexibility). Hospitalisation, RTT-CGI-S, and MPSS subscale scores were used as measures of clinical severity, and these were worse in twin A. Treatment using buspirone shifted twin A from an inflexible to a flexible autonomic profile. This was mirrored in the MPSS scores, which showed a reduction in autonomic and cardiac symptoms following buspirone treatment. Our findings showed that a combination of a co-occurring rs6265 BDNF polymorphism, and worse autonomic and clinical profiles led to a poorer prognosis for twin A compared to twin B. Buspirone was able to shift a rigid autonomic profile to a more flexible one for twin A and thereby prevent cardiac and autonomic symptoms from worsening. The clinical profile for twin A represents a departure from the disorder trajectory typically observed in RTT and underscores the importance of wider genotype profiling and longitudinal objective physiological monitoring alongside measures of clinical symptoms and severity when assessing genotype–phenotype relationships in RTT patients with identical pathogenic mutations. A precision medicine approach that assesses genetic and physiological risk factors can be extended to other neurodevelopmental disorders to monitor risk when genotype–phenotype relationships are not so obvious.
Full article
(This article belongs to the Special Issue Molecular Biology in Drug Design and Precision Therapy)
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Figure 1
<p>Clinical history of twin A and B. A: RTT-anchored Clinical Global Impression Scale for Severity (RTT-CGI-S) scores over time.</p> Full article ">Figure 2
<p>Multi-System Profile of Symptoms Scale (MPSS) scores over time.</p> Full article ">Figure 3
<p>Longitudinal assessment of heart rate variability parameters.</p> Full article ">
<p>Clinical history of twin A and B. A: RTT-anchored Clinical Global Impression Scale for Severity (RTT-CGI-S) scores over time.</p> Full article ">Figure 2
<p>Multi-System Profile of Symptoms Scale (MPSS) scores over time.</p> Full article ">Figure 3
<p>Longitudinal assessment of heart rate variability parameters.</p> Full article ">
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