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24 pages, 3334 KiB  
Article
PPARβ/δ Agonist GW0742 Modulates Microglial and Astroglial Gene Expression in a Rat Model of Temporal Lobe Epilepsy
by Olga E. Zubareva, Adeliya R. Kharisova, Anna I. Roginskaya, Anna A. Kovalenko, Maria V. Zakharova, Alexander P. Schwarz, Denis S. Sinyak and Aleksey V. Zaitsev
Int. J. Mol. Sci. 2024, 25(18), 10015; https://doi.org/10.3390/ijms251810015 (registering DOI) - 17 Sep 2024
Abstract
The role of astroglial and microglial cells in the pathogenesis of epilepsy is currently under active investigation. It has been proposed that the activity of these cells may be regulated by the agonists of peroxisome proliferator-activated nuclear receptors (PPARs). This study investigated the [...] Read more.
The role of astroglial and microglial cells in the pathogenesis of epilepsy is currently under active investigation. It has been proposed that the activity of these cells may be regulated by the agonists of peroxisome proliferator-activated nuclear receptors (PPARs). This study investigated the effects of a seven-day treatment with the PPAR β/δ agonist GW0742 (Fitorine, 5 mg/kg/day) on the behavior and gene expression of the astroglial and microglial proteins involved in the regulation of epileptogenesis in the rat brain within a lithium–pilocarpine model of temporal lobe epilepsy (TLE). TLE resulted in decreased social and increased locomotor activity in the rats, increased expression of astro- and microglial activation marker genes (Gfap, Aif1), pro- and anti-inflammatory cytokine genes (Tnfa, Il1b, Il1rn), and altered expression of other microglial (Nlrp3, Arg1) and astroglial (Lcn2, S100a10) genes in the dorsal hippocampus and cerebral cortex. GW0742 attenuated, but did not completely block, some of these impairments. Specifically, the treatment affected Gfap gene expression in the dorsal hippocampus and Aif1 gene expression in the cortex. The GW0742 injections attenuated the TLE-specific enhancement of Nlrp3 and Il1rn gene expression in the cortex. These results suggest that GW0742 may affect the expression of some genes involved in the regulation of epileptogenesis. Full article
(This article belongs to the Special Issue Epilepsy: From Molecular Basis to Therapy)
21 pages, 6123 KiB  
Article
A Patent-Pending Ointment Containing Extracts of Five Different Plants Showed Antinociceptive and Anti-Inflammatory Mechanisms in Preclinical Studies
by Juan Carlos Barragan-Galvez, Maria Leonor Gonzalez-Rivera, Juan C. Jiménez-Cruz, Araceli Hernandez-Flores, Guadalupe de la Rosa, Martha L. Lopez-Moreno, Eunice Yañez-Barrientos, Michelle Romero-Hernández, Martha Alicia Deveze-Alvarez, Pedro Navarro-Santos, Claudia Acosta-Mata, Mario Alberto Isiordia-Espinoza and Angel Josabad Alonso-Castro
Pharmaceutics 2024, 16(9), 1215; https://doi.org/10.3390/pharmaceutics16091215 (registering DOI) - 17 Sep 2024
Abstract
Background/Objectives: The antinociceptive and anti-inflammatory effects of a patent-pending ointment containing plant extracts from Eucalyptus globulus, Curcuma longa, Hamamelis virginiana, Echinacea purpurea, and Zingiber officinale were evaluated. Methods: Plant extracts were chemically characterized by gas chromatography–mass spectroscopy. [...] Read more.
Background/Objectives: The antinociceptive and anti-inflammatory effects of a patent-pending ointment containing plant extracts from Eucalyptus globulus, Curcuma longa, Hamamelis virginiana, Echinacea purpurea, and Zingiber officinale were evaluated. Methods: Plant extracts were chemically characterized by gas chromatography–mass spectroscopy. The antinociceptive activity of the ointment was assessed using the hot plate, tail flick, and formalin tests, whereas the anti-inflammatory activity was measured using the acute and chronic TPA-induced ear edema tests. Mechanisms of action were evaluated using inhibitors from signaling pathways related to pain response and by using histological analysis and assessing the expression and activity of pro-inflammatory mediators. Results: The ointment showed antinociceptive and anti-inflammatory effects like those observed with diclofenac gel (1.16% v/v) and ketoprofen gel (2.5% v/v). The antinociceptive actions of the ointment are mediated by the possible participation of the opiodergic system and the nitric oxide pathway. The anti-inflammatory response was characterized by a decrease in myeloperoxidase (MPO) activity and by a reduction in ear swelling and monocyte infiltration in the acute inflammation model. In the chronic model, the mechanism of action relied on a decrease in pro-inflammatory mediators such as COX-2, IL-1β, TNF-α, and MPO. An in-silico study with myristic acid, one of the compounds identified in the ointment’s plant mixture, corroborated the in vivo results. Conclusions: The ointment showed antinociceptive activities mediated by the decrease in COX-2 and NO levels, and anti-inflammatory activity due to the reduction in IL-1β and TNFα levels, a reduction in MPO activity, and a decrease in NF-κB and COX-2 expression. Full article
(This article belongs to the Section Pharmacokinetics and Pharmacodynamics)
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Figure 1

Figure 1
<p>GC-MS chromatogram of the ointment prepared with plant extracts. Peaks correspond to the compounds identified and listed in <a href="#pharmaceutics-16-01215-t001" class="html-table">Table 1</a>.</p>
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<p>Results of thermal nociception induced by the TFT (<b>a</b>) and HPT (<b>b</b>). The antinociceptive effect was calculated as the reaction time (seconds) of the mice to heat-induced pain at 0, 1, and 2 h after topical application of the ointment. The vehicle group (V) refers to mice treated with saline solution only. Ketoprofen gel (2.5% <span class="html-italic">w</span>/<span class="html-italic">w</span>) (KET) was used as the reference drug. Bars represent mean values (±SEM) for experimental groups (n = 9), ** <span class="html-italic">p</span> &lt; 0.01, *** <span class="html-italic">p</span> &lt; 0.001, compared to vehicle.</p>
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<p>Ointment’s antinociceptive effect and potential mechanism. (<b>a</b>) The ointment’s pharmacological effect against formalin-induced pain was measured as cumulative licking time (seconds) of mice. Homogenates from the hind paws of the mice were used to measure nitric oxide (NO) production (µM) (<b>b</b>) and electrotransferred to PVDF membrane stained with Ponceau red (<b>c</b>) and immunoblotted with anti-COX2 and anti-β-actin antibodies for densitometric analysis (<b>d</b>,<b>e</b>). The ointment was applied topically 1 h before the intradermal application of formalin. Diclofenac (DIC) 1.16% gel was used as a positive control. The vehicle group (V) was treated with saline solution, and the basal group was the untreated left hind paw. Bars represent mean values (±SEM) for experimental groups (n = 9), ** <span class="html-italic">p</span> &lt; 0.01, *** <span class="html-italic">p</span> &lt; 0.001, compared to the vehicle group (columns 1–2) in (<b>a</b>); a and b mean <span class="html-italic">p</span> &lt; 0.05 compared to the basal and vehicle group, respectively, in (<b>b</b>); and * <span class="html-italic">p</span> &lt; 0.05 compared to the vehicle group in (<b>e</b>).</p>
Full article ">Figure 4
<p>The ointment’s effect on TPA-induced acute ear edema. (<b>a</b>) Inhibition effect calculated as a percentage of anti-inflammatory effect of the ointment topically administered to the right ear 60 min before TPA application (2.5 µg in 20 µL acetone). (<b>b</b>) The ointment’s effect on MPO activity. (<b>c</b>) Representative histological images (H&amp;E staining) of ear biopsies from mice treated with acetone solution (basal), TPA only, treated with the ointment, and diclofenac (DIC) with a dose at 1.16% <span class="html-italic">w</span>/<span class="html-italic">w</span>. Scale bar is indicated below the histological images. Bars represent mean values (±SEM). n = 8, *** <span class="html-italic">p</span> &lt; 0.001 compared to the TPA group in (<b>a</b>), *** <span class="html-italic">p</span> &lt; 0.001 compared to the basal group in (<b>b</b>).</p>
Full article ">Figure 5
<p>The ointment’s protective effects against chronic TPA-induced ear edema. (<b>a</b>) The percentage of anti-inflammatory effect represents ear edema inhibition by topical application of the ointment, which was administered every 48 h for ten days in chronic TPA-induced ear edema (for more information, see the Materials and Methods <a href="#sec2-pharmaceutics-16-01215" class="html-sec">Section 2</a>). (<b>b</b>) Back ear images from mice treated with acetone solution (basal) and treated only with TPA, TPA and diclofenac gel (1.16% <span class="html-italic">w</span>/<span class="html-italic">w</span>), and TPA with ointment. (<b>c</b>) Representative histological images (H&amp;E stain) of ear biopsies from the experimental groups of mice described in (<b>b</b>). The scale bar (200 µm) is denoted below each histological image. Bars in (<b>a</b>) represent mean values (±SEM). n = 8, *** <span class="html-italic">p</span> &lt; 0.001 compared to the vehicle group.</p>
Full article ">Figure 6
<p>Effect of the plant-based ointment on the production of inflammatory mediators in TPA-induced chronic ear edema. Biopsies from mice treated with acetone solution (basal), TPA, TPA and diclofenac (DIC) 1.16% <span class="html-italic">w</span>/<span class="html-italic">w</span>, and TPA and the ointment were homogenized in lysis buffer to obtain supernatants used for measurement of IL-1β (<b>a</b>), TNFα (<b>b</b>), and MPO activity (<b>c</b>). (<b>d</b>) Representative immunoblots of extracts from homogenized biopsies. *** denotes <span class="html-italic">p</span> &lt; 0.05 compared to the basal group.</p>
Full article ">Figure 7
<p>Best poses obtained by molecular docking of myristic acid with the μ-opioid receptor (<b>a</b>) and (<b>b</b>) iNOS.</p>
Full article ">Figure 8
<p>RMSD with the <span class="html-italic">μ-opioid</span> receptor of (<b>a</b>) the Cα skeleton of the myristic acid with the <span class="html-italic">μ-opioid</span> receptor complex (<b>b</b>) in the function of the myristic acid ligand.</p>
Full article ">Figure 9
<p>Number of hydrogen bonds formed in 10 ns of stimulation of the myristic acid–μ-opioid receptor complex.</p>
Full article ">Figure 10
<p>RMSD with iNOS of (<b>a</b>) the Cα skeleton of the myristic acid (in blue) with the iNOS complex with ITU (in black) (<b>b</b>) in function of myristic acid (blue) and ITU (in black) ligands.</p>
Full article ">Figure 11
<p>Number of hydrogen bonds formed in 100 ns of stimulation of the myristic acid–4NOS complex.</p>
Full article ">
31 pages, 7267 KiB  
Article
Euterpe oleracea Mart. Bioactive Molecules: Promising Agents to Modulate the NLRP3 Inflammasome
by Carolina Bordin Davidson, Dana El Soufi El Sabbagh, Amanda Kolinski Machado, Lauren Pappis, Michele Rorato Sagrillo, Sabrina Somacal, Tatiana Emanuelli, Júlia Vaz Schultz, João Augusto Pereira da Rocha, André Flores dos Santos, Solange Binotto Fagan, Ivana Zanella da Silva, Ana Cristina Andreazza and Alencar Kolinski Machado
Biology 2024, 13(9), 729; https://doi.org/10.3390/biology13090729 (registering DOI) - 17 Sep 2024
Abstract
Inflammation is a vital mechanism that defends the organism against infections and restores homeostasis. However, when inflammation becomes uncontrolled, it leads to chronic inflammation. The NLRP3 inflammasome is crucial in chronic inflammatory responses and has become a focal point in research for new [...] Read more.
Inflammation is a vital mechanism that defends the organism against infections and restores homeostasis. However, when inflammation becomes uncontrolled, it leads to chronic inflammation. The NLRP3 inflammasome is crucial in chronic inflammatory responses and has become a focal point in research for new anti-inflammatory therapies. Flavonoids like catechin, apigenin, and epicatechin are known for their bioactive properties (antioxidant, anti-inflammatory, etc.), but the mechanisms behind their anti-inflammatory actions remain unclear. This study aimed to explore the ability of various flavonoids (isolated and combined) to modulate the NLRP3 inflammasome using in silico and in vitro models. Computer simulations, such as molecular docking, molecular dynamics, and MM/GBSA calculations examined the interactions between bioactive molecules and NLRP3 PYD. THP1 cells were treated with LPS + nigericin to activate NLRP3, followed by flavonoid treatment at different concentrations. THP1-derived macrophages were also treated following NLRP3 activation protocols. The assays included colorimetric, fluorometric, microscopic, and molecular techniques. The results showed that catechin, apigenin, and epicatechin had high binding affinity to NLRP3 PYD, similar to the known NLRP3 inhibitor MCC950. These flavonoids, particularly at 1 µg/mL, 0.1 µg/mL, and 0.01 µg/mL, respectively, significantly reduced LPS + nigericin effects in both cell types and decreased pro-inflammatory cytokine, caspase-1, and NLRP3 gene expression, suggesting their potential as anti-inflammatory agents through NLRP3 modulation. Full article
(This article belongs to the Special Issue Biology and Function of Inflammasomes)
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Figure 1
<p>Chromatograms acquired at 280 nm, 320 nm, and 360 nm for non-anthocyanin phenolic compounds and 520 nm for anthocyanin phenolic compounds. Peak 1: gallic acid; peak 2: protocatechuic acid; peak 3: epigallocatechin; peak 4: catechin; peak 5: syringic acid; peak 6: epicatechin; peak 7: taxifolin; peak 8: t-cinnamic acid; peak 9: caffeic acid; peak 10: t-ferulic acid; peak 11: apigenin; peak 12: orienthin; peak 13: kaempferol 3-β-D-glucopyranoside; peak 14: luteolin; peak 15: cyanidin-3-O-glucoside; peak 16: cyanidin-3-O-rutinoside; peak 17: peonidin-3-O-glucoside; peak 18: peonidin-3-O-rutinoside.</p>
Full article ">Figure 2
<p>Açaí extract concentration–response curve—in vitro safety profile evaluation. VERO cells were exposed to different concentrations of free açaí extract for 24, 48, and 72 h of incubation. (<b>A</b>,<b>E</b>,<b>I</b>) Assessment of cellular viability (24 h) and proliferation (48 and 72 h) indexes by MTT assay; (<b>B</b>,<b>F</b>,<b>J</b>) measurement of NO levels after 24, 48, and 72 h of incubation, respectively; (<b>C</b>,<b>G</b>,<b>K</b>) measurement of ROS levels after 24, 48, and 72 h of incubation, respectively; (<b>D</b>,<b>H</b>,<b>L</b>) quantification of dsDNA extracellular indexes after 24, 48, and 72 h of incubation, respectively; NC: negative control (cells under conventional cell culture condition); PC: cells exposed to 200 µM of H<sub>2</sub>O<sub>2</sub> for MTT, DCFH-DA, and PicoGreen assays and 10 µM of sodium nitroprusside for NO determination assay; statistical analysis was performed by one-way ANOVA followed by Tukey post hoc. Results with <span class="html-italic">p</span> &lt; 0.05 were considered significant. * <span class="html-italic">p</span> &lt; 0.05; ** <span class="html-italic">p</span> &lt; 0.01; *** <span class="html-italic">p</span> &lt; 0.001; **** <span class="html-italic">p</span> &lt; 0.0001.</p>
Full article ">Figure 3
<p>Interactions between NLRP3 (PYD domain) and catechin, apigenin, epicatechin, and MCC950 with pH 7.4 and 6.5. (<b>A</b>–<b>D</b>,<b>I</b>–<b>L</b>) Interactions between catechin, apigenin, epicatechin, and MCC950, respectively, with NLRP3 PYD domain; (<b>E</b>–<b>H</b>,<b>M</b>–<b>P</b>) 2D map of the interaction of NLRP3 with catechin, apigenin, epicatechin, and MCC950 and amino acid residues and bond types.</p>
Full article ">Figure 4
<p>RMSD of the complexes formed between the PYD domain of NLRP3 and the ligands MCC950, apigenin, catechin, epicatechin, and the APO (unbound) form of the protein (without ligand) over 100 ns of molecular dynamics simulation. It is observed that the complex with MCC950 presented greater structural variation, with the RMSD reaching approximately 5 Å, indicating greater conformational flexibility. Apigenin presented the lowest RMSD, around 1.26 Å, suggesting greater stabilization of the protein. Catechin and epicatechin exhibited intermediate RMSD, ranging from 2.10 to 2.16 Å, while the APO form presented moderate fluctuations, with RMSD around 2.20 Å.</p>
Full article ">Figure 5
<p>Root Mean Square Fluctuation (RMSF) of the complexes formed between the PYD domain of NLRP3 and the ligands MCC950, apigenin, catechin, epicatechin, and the APO form of the protein (without ligand). The fluctuation was calculated over 100 ns of molecular dynamics simulation. Catechin showed the highest fluctuations in residues, particularly in the terminal and central regions, suggesting greater conformational flexibility. Apigenin exhibited moderate fluctuations, while epicatechin and MCC950 displayed lower residual fluctuation, suggesting more efficient conformational stabilization in these critical regions. The APO form exhibited the lowest variation, reflecting the absence of interactions with ligands. Stabilization in the regions between Leu20 and Pro40 was observed in the MCC950 and epicatechin complexes, which may indicate more stable interactions in these key residues.</p>
Full article ">Figure 6
<p>Energy decomposition per residue for the complexes formed between the PYD domain of NLRP3 and the ligands MCC950, apigenin, catechin, and epicatechin. The energetic contribution of each residue is presented in kcal/mol, highlighting the most critical residues for the stabilization of the complexes. For MCC950, residues Gln33, Pro32, Pro38, and Leu39 showed significant contributions, with energy values below −2 kcal/mol, indicating strong interactions at these sites. For apigenin, residues Pro31, Pro32, Cys36, and Pro38 were the main energetic contributors, while the catechin complexes presented more relevant interactions at residues Lys21, Lys22, and Val18. Lastly, for epicatechin, residues Cys36, Pro38, Leu39, and Arg41 were highlighted as the main stabilizers.</p>
Full article ">Figure 7
<p>Bioactive molecule concentration curve—in vitro safety profile evaluation. VERO cells were exposed to different concentrations of catechin, apigenin, and epicatechin for 24 h of incubation. (<b>A</b>,<b>E</b>,<b>I</b>) Assessment of cellular viability (24 h) indexes by MTT assay; (<b>B</b>,<b>F</b>,<b>J</b>) measurement of NO levels after 24 h of incubation; (<b>C</b>,<b>G</b>,<b>K</b>) measurement of ROS levels after 24 h; (<b>D</b>,<b>H</b>,<b>L</b>) quantification of dsDNA extracellular indexes after 24 h of incubation; NC: negative control (cells under conventional cell culture condition); PC: cells exposed to 200 µM of H<sub>2</sub>O<sub>2</sub> for MTT, DCFH-DA, and PicoGreen assays and 10 µM of sodium nitroprusside for NO determination assay; statistical analysis was performed by one-way ANOVA followed by Tukey post hoc. Results with <span class="html-italic">p</span> &lt; 0.05 were considered significant. * <span class="html-italic">p</span> &lt; 0.05; ** <span class="html-italic">p</span> &lt; 0.01; *** <span class="html-italic">p</span> &lt; 0.001; **** <span class="html-italic">p</span> &lt; 0.0001.</p>
Full article ">Figure 8
<p>Anti-inflammatory capacity of catechin, apigenin, and epicatechin in monocytes. LPS + nigericin was used as the NLRP3 activation agent; MCC950 was used as a known NLRP3 inhibitor agent. (<b>A</b>,<b>E</b>,<b>I</b>) Assessment of cellular viability indexes by MTT assay; (<b>B</b>,<b>F</b>,<b>J</b>) indirect determination of NO levels; (<b>C</b>,<b>G</b>,<b>K</b>) qualitative measurement of ROS production; (<b>D</b>,<b>H</b>,<b>L</b>) quantification of dsDNA extracellular indexes. NC: negative control (cells under conventional cell culture condition); statistical analysis was performed by one-way ANOVA followed by Tukey post hoc. Results with <span class="html-italic">p</span> &lt; 0.05 were considered significant. * represents comparison to the negative control; # represents comparison to LPS positive control; * <span class="html-italic">p</span> &lt; 0.05; **** <span class="html-italic">p</span> &lt; 0.0001; ## &lt; 0.01; ### &lt; 0.001; #### &lt; 0.0001.</p>
Full article ">Figure 9
<p>Combined bioactive molecules—in vitro safety profile evaluation. VERO cells were exposed to different combinations of bioactive molecules for 24, 48, and 72 h of incubation. (<b>A</b>,<b>E</b>,<b>I</b>) Assessment of cellular viability (24 h) and proliferation (48 and 72 h) indexes by MTT assay; (<b>B</b>,<b>F</b>,<b>J</b>) measurement of NO levels after 24, 48, and 72 h of incubation, respectively; (<b>C</b>,<b>G</b>,<b>K</b>) measurement of ROS levels after 24, 48, and 72 h of incubation, respectively; (<b>D</b>,<b>H</b>,<b>L</b>) quantification of dsDNA extracellular indexes after 24, 48, and 72 h of incubation, respectively—NC: negative control (cells under conventional cell culture condition); PC: cells exposed to 200 µM of H<sub>2</sub>O<sub>2</sub> for MTT, DCFH-DA, and PicoGreen assays and 10 µM of sodium nitroprusside for NO determination assay; (<b>M</b>) assessment of genotoxic effect; (<b>N</b>) measurement of hemolysis—PC: red blood cells were lysed with dH<sub>2</sub>O. C: catechin; Api: apigenin; and EC: epicatechin. Statistical analysis was performed by one-way ANOVA followed by Tukey post hoc. # represents comparison to hemolysis positive control. Results with <span class="html-italic">p</span> &lt; 0.05 were considered significant. * <span class="html-italic">p</span> &lt; 0.05; ** <span class="html-italic">p</span> &lt; 0.01; *** <span class="html-italic">p</span> &lt; 0.001; **** <span class="html-italic">p</span> &lt; 0.0001; #### &lt; 0.0001.</p>
Full article ">Figure 10
<p>Inflammation based on the NLRP3 inflammasome mechanism. LPS + nigericin was used as the activation agent; MCC950 was used as a known inhibitor agent. Left side—THP-1 differentiation to macrophages: (<b>A</b>) microscopical analysis of THP1 monocytes without any treatment; (<b>B</b>) THP1-derived macrophages generated by PMA exposure. Right side—experimental analyses of (<b>C</b>) cell viability by MTT; (<b>D</b>) NO indexes; (<b>E</b>) ROS levels; and (<b>F</b>) measurement of the extracellular dsDNA index. NC: negative control (cells under conventional cell culture condition). C: catechin; Api: apigenin; and EC: epicatechin. Statistical analysis was performed by one-way ANOVA followed by Tukey post hoc. Results with <span class="html-italic">p</span> &lt; 0.05 were considered significant. * represents comparison to the negative control; # represents comparison to LPS positive control; * <span class="html-italic">p</span> &lt; 0.05; ** <span class="html-italic">p</span> &lt; 0.01; *** <span class="html-italic">p</span> &lt; 0.001; **** <span class="html-italic">p</span> &lt; 0.0001; #### &lt; 0.0001. Magnification: 20×.</p>
Full article ">Figure 11
<p>Anti-inflammatory capacity of combined bioactive molecules in macrophages. (<b>A</b>) Analysis of cell morphology by optical microscopy after each treatment. (<b>B</b>) Lactate levels after each treatment. (<b>C</b>) Caspase-1 gene expression after each treatment. (<b>D</b>) NLRP3 gene expression after each treatment. (<b>E</b>) IL-1β gene expression after each treatment. (<b>F</b>) IL-6 gene expression after each treatment. (<b>G</b>) TNF-α gene expression after each treatment. (<b>H</b>) IL-10 gene expression after each treatment. NC: negative control (cells under conventional cell culture condition). C: catechin; EC: epicatechin. Statistical analysis was performed by one-way ANOVA followed by Tukey post hoc. Results with <span class="html-italic">p</span> &lt; 0.05 were considered significant. * represents comparison to the negative control; # represents comparison to LPS positive control; * <span class="html-italic">p</span> &lt; 0.05; ** <span class="html-italic">p</span> &lt; 0.01; *** <span class="html-italic">p</span> &lt; 0.001; **** <span class="html-italic">p</span> &lt; 0.0001; ## &lt; 0.01; ### &lt; 0.001; #### &lt; 0.0001. Magnification: 20×.</p>
Full article ">
14 pages, 2039 KiB  
Article
Metabolomic Effects of Liraglutide Therapy on the Plasma Metabolomic Profile of Patients with Obesity
by Assim A. Alfadda, Anas M. Abdel Rahman, Hicham Benabdelkamel, Reem AlMalki, Bashayr Alsuwayni, Abdulaziz Alhossan, Madhawi M. Aldhwayan, Ghalia N. Abdeen, Alexander Dimitri Miras and Afshan Masood
Metabolites 2024, 14(9), 500; https://doi.org/10.3390/metabo14090500 (registering DOI) - 17 Sep 2024
Abstract
Background: Liraglutide, a long-acting glucagon-like peptide-1 receptor agonist (GLP1RA), is a well-established anti-diabetic drug, has also been approved for the treatment of obesity at a dose of 3 mg. There are a limited number of studies in the literature that have looked at [...] Read more.
Background: Liraglutide, a long-acting glucagon-like peptide-1 receptor agonist (GLP1RA), is a well-established anti-diabetic drug, has also been approved for the treatment of obesity at a dose of 3 mg. There are a limited number of studies in the literature that have looked at changes in metabolite levels before and after liraglutide treatment in patients with obesity. To this end, in the present study we aimed to explore the changes in the plasma metabolomic profile, using liquid chromatography-high resolution mass spectrometry (LC-HRMS) in patients with obesity. Methods: A single-center prospective study was undertaken to evaluate the effectiveness of 3 mg liraglutide therapy in twenty-three patients (M/F: 8/15) with obesity, mean BMI 40.81 ± 5.04 kg/m2, and mean age of 36 ± 10.9 years, in two groups: at baseline (pre-treatment) and after 12 weeks of treatment (post-treatment). An untargeted metabolomic profiling was conducted in plasma from the pre-treatment and post-treatment groups using LC-HRMS, along with bioinformatics analysis using ingenuity pathway analysis (IPA). Results: The metabolomics analysis revealed a significant (FDR p-value ≤ 0.05, FC 1.5) dysregulation of 161 endogenous metabolites (97 upregulated and 64 downregulated) with distinct separation between the two groups. Among the significantly dysregulated metabolites, the majority of them were identified as belonging to the class of oxidized lipids (oxylipins) that includes arachidonic acid and its derivatives, phosphorglycerophosphates, N-acylated amino acids, steroid hormones, and bile acids. The biomarker analysis conducted using MetaboAnalyst showed PGP (a21:0/PG/F1alpha), an oxidized lipid, as the first metabolite among the list of the top 15 biomarkers, followed by cysteine and estrone. The IPA analysis showed that the dysregulated metabolites impacted the pathway related to cell signaling, free radical scavenging, and molecular transport, and were focused around the dysregulation of NF-κB, ERK, MAPK, PKc, VEGF, insulin, and pro-inflammatory cytokine signaling pathways. Conclusions: The findings suggest that liraglutide treatment reduces inflammation and modulates lipid metabolism and oxidative stress. Our study contributes to a better understanding of the drug’s multifaceted impact on overall metabolism in patients with obesity. Full article
(This article belongs to the Special Issue Metabolomics in Human Diseases and Health)
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<p>(<b>A</b>) Receiver operating characteristic (ROC) curve utilizing PLS-DA as the classification and feature ranking method. The top 15 variants had an area under the curve (AUC) of 0.852. (<b>B</b>) Frequency plot showing the top 15 significantly dysregulated metabolites in the pre- and post-liraglutide treatment groups. ROC curves are shown of individual metabolite biomarkers: (<b>C</b>) N-linoleoyl tryptophan, with an AUC of 0.881, and box plot (<span class="html-italic">p</span> ≤ 0.05 and fold change ≥ 1.5), where red represents the post-liraglutide treatment group and green represents the pre-liraglutide treatment group; and (<b>D</b>) epinephrine glucuronide, with an AUC of 0.849, and box plot (<span class="html-italic">p</span> ≤ 0.05 and fold change ≥ 1.5), where red represents the post-liraglutide treatment group and green represents the pre-liraglutide treatment group.</p>
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<p>Schematic representation of the (<b>A</b>) highest scoring network pathways depicting the involvement of the differentially regulated metabolites between the pre- and post-liraglutide treatment groups. The dotted lines indicate indirect relationships, and the straight lines indicate direct relationships. The network pathways identified between the two groups were related to cell signalling, free radical scavenging, and molecular transport, with a score of 36 and 14 focus molecules (represented in bold <a href="#app1-metabolites-14-00500" class="html-app">Supplementary Table S4</a>). The interaction networks were generated through IPA (QIAGEN, Aarhus, Denmark). (<b>B</b>) The top canonical pathways dysregulated after 12 weeks of treatment with liraglutide.</p>
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<p>Schematic representation of the (<b>A</b>) highest scoring network pathways depicting the involvement of the differentially regulated metabolites between the pre- and post-liraglutide treatment groups. The dotted lines indicate indirect relationships, and the straight lines indicate direct relationships. The network pathways identified between the two groups were related to cell signalling, free radical scavenging, and molecular transport, with a score of 36 and 14 focus molecules (represented in bold <a href="#app1-metabolites-14-00500" class="html-app">Supplementary Table S4</a>). The interaction networks were generated through IPA (QIAGEN, Aarhus, Denmark). (<b>B</b>) The top canonical pathways dysregulated after 12 weeks of treatment with liraglutide.</p>
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13 pages, 718 KiB  
Review
Are Small Molecules Effective in Treating Inflammatory Pouch Disorders Following Ileal Pouch-Anal Anastomosis for Ulcerative Colitis? Here Is Where We Stand
by Antonietta Gerarda Gravina, Raffaele Pellegrino, Giovanna Palladino, Giuseppe Imperio, Francesco Calabrese, Andrea Pasta, Edoardo Giovanni Giannini, Alessandro Federico and Giorgia Bodini
Biomolecules 2024, 14(9), 1164; https://doi.org/10.3390/biom14091164 (registering DOI) - 17 Sep 2024
Viewed by 118
Abstract
Ulcerative colitis (UC) management encompasses conventional and advanced treatments, including biological therapy and small molecules. Surgery, particularly in the form of ileal pouch-anal anastomosis (IPAA), is indicated in cases of refractory/severe disease. IPAA can lead to acute complications (e.g., acute pouchitis) as well [...] Read more.
Ulcerative colitis (UC) management encompasses conventional and advanced treatments, including biological therapy and small molecules. Surgery, particularly in the form of ileal pouch-anal anastomosis (IPAA), is indicated in cases of refractory/severe disease. IPAA can lead to acute complications (e.g., acute pouchitis) as well as late complications, including chronic inflammatory disorders of the pouch. Chronic pouchitis, including the antibiotic-dependent (CADP) and antibiotic-refractory (CARP) forms, represents a significant and current therapeutic challenge due to the substantial need for evidence regarding viable treatment options. Biological therapies have shown promising results, with infliximab, adalimumab, ustekinumab, and vedolizumab demonstrating some efficacy in chronic pouchitis; however, robust randomized clinical trials are only available for vedolizumab. This narrative review focuses on the evidence concerning small molecules in chronic pouchitis, specifically Janus kinase (JAK) inhibitors and sphingosine-1-phosphate receptor (S1P-R) modulators. According to the preliminary studies and reports, Tofacitinib shows a potential effectiveness in CARP. Upadacitinib presents variable outcomes from the case series, necessitating further evaluation. Filgotinib and ozanimod demonstrate anecdotal efficacy. This review underscores the need for high-quality studies and real-world registries to develop robust guidelines for advanced therapies in post-IPAA inflammatory disorders, supported by vigilant clinical monitoring and ongoing education from international IBD specialist societies. Full article
(This article belongs to the Special Issue Molecular Advances in Inflammatory Bowel Disease)
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<p>Rates of clinical response (<b>A</b>) and remission (<b>B</b>) reported in studies exploring the efficacy of tofacitinib in treating inflammatory pouch disorders. The data are expressed as a percentage rate and as the number of patients who achieved the outcome of interest (i.e., clinical response or remission) out of the total number of patients included in the analysis. The rate of 50% is indicated on the <span class="html-italic">x</span>-axis by a vertical dashed grey line. The superscripts related to each study explain the interpretation provided by each study regarding the rates of clinical response and clinical remission, and, specifically: (1) Clinical remission was defined as being steroid-free and antibiotic-free at week 8 (±4 weeks) and week 52 (±8 weeks) with a modified pouchitis disease activity index (mPDAI) &lt;5 and, in cases where endoscopic control was lacking, as having an isolated clinical subscore &lt;2. Clinical response was defined at week 8 (±4 weeks) and week 52 (±8 weeks) as being steroid-free with a reduction in mPDAI &gt;4 at week 8 compared to baseline, with a reduction in mPDAI &gt;1. In cases where endoscopic assessment was lacking, clinical response was indicated by a clinical subscore &gt;1 at week 8 with a reduction of at least 1 point from the baseline score. (2) Clinical response at three months was defined as steroid- and antibiotic-free with a reduction in mPDAI of at least one point from baseline. Clinical response was defined at twelve months as a reduction in mPDAI of at least two points compared to baseline. Remission, both at three months and twelve months, was defined as an mPDAI score of 0. (3) Clinical response, assessed at month 3 (±2 months) and month 12 (±2 months), was evaluated as an improvement of at least two points from the baseline mPDAI. (4) Clinical response at 8 weeks was defined as a reduction of at least two points in the mPDAI compared to baseline with at least a one-point reduction in the endoscopic subscore. Clinical remission was defined as an mPDAI &lt;5 compared to baseline with a reduction of at least two points compared to baseline and changes in clinical and endoscopic scores of the PDAI subscores, faecal calprotectin, and the 10-point Cleveland global quality of life scores. (5) Clinical response was defined as a reduction of at least two points in the clinical PDAI compared to baseline at week 8. Clinical remission was defined as an mPDAI &lt;5 compared to baseline. The references related to the studies shown in the figure are as follows: Uzzan et al. (2023) [<a href="#B31-biomolecules-14-01164" class="html-bibr">31</a>], Ribaldone et al. (2023) [<a href="#B32-biomolecules-14-01164" class="html-bibr">32</a>], Akiyama et al. (2023) [<a href="#B33-biomolecules-14-01164" class="html-bibr">33</a>], Syal et al. (2023) [<a href="#B34-biomolecules-14-01164" class="html-bibr">34</a>], Khoo et al. (2024) [<a href="#B35-biomolecules-14-01164" class="html-bibr">35</a>].</p>
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17 pages, 8104 KiB  
Article
Potential Plasma Proteins (LGALS9, LAMP3, PRSS8 and AGRN) as Predictors of Hospitalisation Risk in COVID-19 Patients
by Thomas McLarnon, Darren McDaid, Seodhna M. Lynch, Eamonn Cooper, Joseph McLaughlin, Victoria E. McGilligan, Steven Watterson, Priyank Shukla, Shu-Dong Zhang, Magda Bucholc, Andrew English, Aaron Peace, Maurice O’Kane, Martin Kelly, Manav Bhavsar, Elaine K. Murray, David S. Gibson, Colum P. Walsh, Anthony J. Bjourson and Taranjit Singh Rai
Biomolecules 2024, 14(9), 1163; https://doi.org/10.3390/biom14091163 (registering DOI) - 17 Sep 2024
Viewed by 165
Abstract
Background: The COVID-19 pandemic, caused by the novel coronavirus SARS-CoV-2, has posed unprecedented challenges to healthcare systems worldwide. Here, we have identified proteomic and genetic signatures for improved prognosis which is vital for COVID-19 research. Methods: We investigated the proteomic and genomic profile [...] Read more.
Background: The COVID-19 pandemic, caused by the novel coronavirus SARS-CoV-2, has posed unprecedented challenges to healthcare systems worldwide. Here, we have identified proteomic and genetic signatures for improved prognosis which is vital for COVID-19 research. Methods: We investigated the proteomic and genomic profile of COVID-19-positive patients (n = 400 for proteomics, n = 483 for genomics), focusing on differential regulation between hospitalised and non-hospitalised COVID-19 patients. Signatures had their predictive capabilities tested using independent machine learning models such as Support Vector Machine (SVM), Random Forest (RF) and Logistic Regression (LR). Results: This study has identified 224 differentially expressed proteins involved in various inflammatory and immunological pathways in hospitalised COVID-19 patients compared to non-hospitalised COVID-19 patients. LGALS9 (p-value < 0.001), LAMP3 (p-value < 0.001), PRSS8 (p-value < 0.001) and AGRN (p-value < 0.001) were identified as the most statistically significant proteins. Several hundred rsIDs were queried across the top 10 significant signatures, identifying three significant SNPs on the FSTL3 gene showing a correlation with hospitalisation status. Conclusions: Our study has not only identified key signatures of COVID-19 patients with worsened health but has also demonstrated their predictive capabilities as potential biomarkers, which suggests a staple role in the worsened health effects caused by COVID-19. Full article
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<p>Differentially expressed proteins in hospitalised patients. (<b>A</b>). Heatmap with patients being grouped in columns according to their hospitalisation status, severity status according to the WHO scale (1–4 mild, 5–10 severe), and age. Proteins clustered as rows, with the significant threshold for proteins set to log2FC &gt; 0.5 and a <span class="html-italic">p</span>-value &lt; 0.01. (<b>B</b>). Volcano plot of differentially expressed proteins in hospitalised patients compared to non-hospitalised patients, ranked according to their −log10(<span class="html-italic">p</span>-Value) on the <span class="html-italic">y</span>-axis and log2FC on the <span class="html-italic">x</span>-axis. The significance threshold was set to log2FC &gt; 0.5 and <span class="html-italic">p</span>-value &lt; 0.05. (<b>C</b>). Violin box plots of LGLAS9, LAMP3, PRSS8 and AGRN, depicting NPX regulation between hospitalised and non-hospitalised patients.</p>
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<p>Differentially expressed proteins in hospitalised patients. (<b>A</b>). Heatmap with patients being grouped in columns according to their hospitalisation status, severity status according to the WHO scale (1–4 mild, 5–10 severe), and age. Proteins clustered as rows, with the significant threshold for proteins set to log2FC &gt; 0.5 and a <span class="html-italic">p</span>-value &lt; 0.01. (<b>B</b>). Volcano plot of differentially expressed proteins in hospitalised patients compared to non-hospitalised patients, ranked according to their −log10(<span class="html-italic">p</span>-Value) on the <span class="html-italic">y</span>-axis and log2FC on the <span class="html-italic">x</span>-axis. The significance threshold was set to log2FC &gt; 0.5 and <span class="html-italic">p</span>-value &lt; 0.05. (<b>C</b>). Violin box plots of LGLAS9, LAMP3, PRSS8 and AGRN, depicting NPX regulation between hospitalised and non-hospitalised patients.</p>
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<p>COVID-19 Separation and Signalling Differences. (<b>A</b>). Principal Component analysis of COVID-19 patients using all proteomic values. The <span class="html-italic">x</span>-axis represents PC1, which accounts for the most variance, and the <span class="html-italic">y</span>-axis represents PC2, which accounts for the second most variance, labelled according to hospitalisation status. (<b>B</b>). 2D-proteomic scatter plot depicting NPX regulation of LGALS9 on the <span class="html-italic">x</span>-axis and LAMP3 on the <span class="html-italic">y</span>-axis for each patient, labelled according to their hospitalisation status. (<b>C</b>). 3D-proteomic scatter plot depicting NPX regulation of LAMP-3 on the <span class="html-italic">x</span>-axis, LGALS9 on the <span class="html-italic">y</span>-axis and PRSS8 on the <span class="html-italic">z</span>-axis for each patient, labelled according to their hospitalisation status. (<b>D</b>). Protein-protein interaction network generated from stringDB demonstrating the relationships between LGALS9, LAMP3, PRSS8 and AGRN. (<b>E</b>). Pathway analysis plot showing the top 10 differentially expressed signalling pathways in hospitalised COVID-19 patients compared to non-hospitalised COVID-19 patients. Fold enrichment was measured on the <span class="html-italic">x</span>-axis, GO terms were listed on the <span class="html-italic">y</span>-axis, and the size and colour of the data points for each term were dependent on their −log10(<span class="html-italic">p</span>-value).</p>
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<p>COVID-19 Separation and Signalling Differences. (<b>A</b>). Principal Component analysis of COVID-19 patients using all proteomic values. The <span class="html-italic">x</span>-axis represents PC1, which accounts for the most variance, and the <span class="html-italic">y</span>-axis represents PC2, which accounts for the second most variance, labelled according to hospitalisation status. (<b>B</b>). 2D-proteomic scatter plot depicting NPX regulation of LGALS9 on the <span class="html-italic">x</span>-axis and LAMP3 on the <span class="html-italic">y</span>-axis for each patient, labelled according to their hospitalisation status. (<b>C</b>). 3D-proteomic scatter plot depicting NPX regulation of LAMP-3 on the <span class="html-italic">x</span>-axis, LGALS9 on the <span class="html-italic">y</span>-axis and PRSS8 on the <span class="html-italic">z</span>-axis for each patient, labelled according to their hospitalisation status. (<b>D</b>). Protein-protein interaction network generated from stringDB demonstrating the relationships between LGALS9, LAMP3, PRSS8 and AGRN. (<b>E</b>). Pathway analysis plot showing the top 10 differentially expressed signalling pathways in hospitalised COVID-19 patients compared to non-hospitalised COVID-19 patients. Fold enrichment was measured on the <span class="html-italic">x</span>-axis, GO terms were listed on the <span class="html-italic">y</span>-axis, and the size and colour of the data points for each term were dependent on their −log10(<span class="html-italic">p</span>-value).</p>
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<p>Univariate machine learning predictions for hospitalisation risk. Univariate ROC curves from SVM, LR and RF models for LGALS9, AGRN, PRSS8 and LAMP3 with labelled AUC scores and 95% confidence intervals shaded on the plot by bootstrap sampling the sensitivities and specificities 500 times.</p>
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<p>Univariate machine learning predictions for hospitalisation risk. Univariate ROC curves from SVM, LR and RF models for LGALS9, AGRN, PRSS8 and LAMP3 with labelled AUC scores and 95% confidence intervals shaded on the plot by bootstrap sampling the sensitivities and specificities 500 times.</p>
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<p>Feature-selected machine learning predictions for hospitalisation risk. (<b>A</b>). Variable importance plots of the RFE-SVM, RFE-RF and LASSO-LR models, ranking the top 10 most important features within the model according to their importance score. (<b>B</b>). Feature-selected ROC curves from RFE-SVM, RFE-RF and LASSO-LR using the optimal features, labelled AUC scores and 95% confidence intervals shaded on the plot by bootstrap sampling the sensitivities and specificities 500 times. (<b>C</b>). Confusion matrices generated for the RFE-SVM, RFE-RF and LASSO-LR models by comparing their actual predictions of hospitalised and non-hospitalised patients on unseen data not used for model training.</p>
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<p>Feature-selected machine learning predictions for hospitalisation risk. (<b>A</b>). Variable importance plots of the RFE-SVM, RFE-RF and LASSO-LR models, ranking the top 10 most important features within the model according to their importance score. (<b>B</b>). Feature-selected ROC curves from RFE-SVM, RFE-RF and LASSO-LR using the optimal features, labelled AUC scores and 95% confidence intervals shaded on the plot by bootstrap sampling the sensitivities and specificities 500 times. (<b>C</b>). Confusion matrices generated for the RFE-SVM, RFE-RF and LASSO-LR models by comparing their actual predictions of hospitalised and non-hospitalised patients on unseen data not used for model training.</p>
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<p>Genotyping analysis on key signatures. Bar charts demonstrating the percentage of each patient (hospitalised vs. non-hospitalised) and their genotypes, respective to each rsID. Where 0/0 represents the homozygous reference genotype, 0/1 represents the heterozygous genotype and 1/1 represents the homozygous alternative genotype. (<b>A</b>). <span class="html-italic">FSTL3</span> rs1046253 (<b>B</b>). <span class="html-italic">FSTL3</span> rs2057713. (<b>C</b>). <span class="html-italic">FSTL3</span> rs2057714.</p>
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17 pages, 4662 KiB  
Article
Evaluating the Role of Vitamin D in Alleviating Chronic Pruritus: A Meta-Analysis
by Chen-Pi Li, Shin-Chuan Huang, Yao Hsiao and Ru-Yin Tsai
Int. J. Mol. Sci. 2024, 25(18), 9983; https://doi.org/10.3390/ijms25189983 (registering DOI) - 16 Sep 2024
Viewed by 238
Abstract
Chronic pruritus is a distressing condition that significantly impacts patients’ quality of life. Recent research has increasingly focused on the potential role of vitamin D, given its immunomodulatory properties, in managing this condition. This meta-analysis seeks to systematically assess the effectiveness of vitamin [...] Read more.
Chronic pruritus is a distressing condition that significantly impacts patients’ quality of life. Recent research has increasingly focused on the potential role of vitamin D, given its immunomodulatory properties, in managing this condition. This meta-analysis seeks to systematically assess the effectiveness of vitamin D supplementation in alleviating chronic pruritus across diverse clinical contexts. We conducted an extensive search through multiple databases, covering literature up to July 2024, to identify relevant randomized controlled trials (RCTs) that evaluated the effect of vitamin D on chronic pruritus. Eligible studies were those that provided data on changes in pruritus severity, as measured by standardized tools, before and after vitamin D treatment. The data were synthesized using a random-effects model to address variability among the studies. This meta-analysis is registered with PROSPERO (registration number: CRD42024579353). The findings indicate that vitamin D supplementation is associated with a significant reduction in pruritus severity, the skin lesion area, and levels of inflammatory cytokines, including tumor necrosis factor (TNF), interleukin-6 (IL-6), and high-sensitivity C-reactive protein (hs-CRP), compared to controls. These results suggest that vitamin D could be a promising therapeutic option for chronic pruritus, though further rigorous studies are required to validate these findings and to elucidate the mechanisms involved. Full article
(This article belongs to the Special Issue Targeted Therapy for Immune Diseases)
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<p>A flowchart illustrating the study selection process for the systematic review and meta-analysis on the effects of vitamin D in reducing chronic pruritus in adults with various dermatological conditions. Out of 575 identified records, only 9 met the eligibility criteria and were included in the final review.</p>
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<p>Evaluation of the methodological quality of the included trials. (<b>A</b>) Individual risk of bias assessment for each selected study, based on the Rob tool. (<b>B</b>) Overall risk of bias summarized as a percentage, considering intention-to-treat and per-protocol analyses. The primary sources of high risk of bias across the studies were deviations from intended interventions, followed by issues related to missing outcome data and deficiencies in the randomization process [<a href="#B2-ijms-25-09983" class="html-bibr">2</a>,<a href="#B3-ijms-25-09983" class="html-bibr">3</a>,<a href="#B15-ijms-25-09983" class="html-bibr">15</a>,<a href="#B17-ijms-25-09983" class="html-bibr">17</a>,<a href="#B34-ijms-25-09983" class="html-bibr">34</a>,<a href="#B35-ijms-25-09983" class="html-bibr">35</a>,<a href="#B36-ijms-25-09983" class="html-bibr">36</a>,<a href="#B37-ijms-25-09983" class="html-bibr">37</a>,<a href="#B38-ijms-25-09983" class="html-bibr">38</a>].</p>
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<p>(<b>A</b>) displays the overall impact of vitamin D on chronic pruritus, as measured by the visual analog scale, compared to the placebo. (<b>B</b>–<b>D</b>) show subgroup analyses corresponding to (<b>A</b>): (<b>B</b>) examines the effect based on the duration of treatment, (<b>C</b>) focuses on the specific disease diagnosis, and (<b>D</b>) considers the method of treatment administration. The pruritus-relieving effect of vitamin D is represented by squares, which indicate the standardized mean difference, with the squares shifting to the left to signify a reduction in pruritus. The horizontal lines through the squares depict the 95% confidence intervals, while the diamond symbol represents the pooled effect size [<a href="#B2-ijms-25-09983" class="html-bibr">2</a>,<a href="#B3-ijms-25-09983" class="html-bibr">3</a>,<a href="#B15-ijms-25-09983" class="html-bibr">15</a>,<a href="#B17-ijms-25-09983" class="html-bibr">17</a>,<a href="#B34-ijms-25-09983" class="html-bibr">34</a>,<a href="#B35-ijms-25-09983" class="html-bibr">35</a>,<a href="#B36-ijms-25-09983" class="html-bibr">36</a>,<a href="#B37-ijms-25-09983" class="html-bibr">37</a>,<a href="#B38-ijms-25-09983" class="html-bibr">38</a>].</p>
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<p>Presents a forest plot that highlights the effects of vitamin D supplementation. The plot is divided into four sections for ease of interpretation: (<b>A</b>) shows the effect on the skin lesion area, (<b>B</b>) depicts changes in TNF levels, (<b>C</b>) assesses alterations in IL-6 levels, and (<b>D</b>) evaluates the impact on hs-CRP. The horizontal lines extending from the squares represent the 95% confidence intervals, while the diamond symbols indicate the overall effect sizes [<a href="#B2-ijms-25-09983" class="html-bibr">2</a>,<a href="#B3-ijms-25-09983" class="html-bibr">3</a>,<a href="#B15-ijms-25-09983" class="html-bibr">15</a>,<a href="#B35-ijms-25-09983" class="html-bibr">35</a>,<a href="#B36-ijms-25-09983" class="html-bibr">36</a>,<a href="#B37-ijms-25-09983" class="html-bibr">37</a>,<a href="#B38-ijms-25-09983" class="html-bibr">38</a>].</p>
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<p>Illustrates the overall effect of vitamin D3 on chronic pruritus, as assessed by the visual analog scale, in comparison to the placebo. The horizontal lines through the squares depict the 95% confidence intervals, while the diamond symbol represents the pooled effect size [<a href="#B2-ijms-25-09983" class="html-bibr">2</a>,<a href="#B15-ijms-25-09983" class="html-bibr">15</a>,<a href="#B35-ijms-25-09983" class="html-bibr">35</a>,<a href="#B36-ijms-25-09983" class="html-bibr">36</a>,<a href="#B37-ijms-25-09983" class="html-bibr">37</a>,<a href="#B38-ijms-25-09983" class="html-bibr">38</a>].</p>
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<p>The lines represent the confidence intervals around the effect estimates, indicating the range within which the true effect size is likely to fall. Each circle corresponds to an individual study included in the meta-analysis, with the size of the circle potentially reflecting the study’s weight or sample size. Larger circles denote studies with greater weight or larger sample sizes. The diamond symbol signifies the overall effect estimate from the meta-analysis. The center of the diamond marks the pooled effect size, and the width of the diamond indicates the confidence interval for this estimate [<a href="#B2-ijms-25-09983" class="html-bibr">2</a>,<a href="#B3-ijms-25-09983" class="html-bibr">3</a>,<a href="#B15-ijms-25-09983" class="html-bibr">15</a>,<a href="#B35-ijms-25-09983" class="html-bibr">35</a>,<a href="#B36-ijms-25-09983" class="html-bibr">36</a>,<a href="#B37-ijms-25-09983" class="html-bibr">37</a>,<a href="#B38-ijms-25-09983" class="html-bibr">38</a>].</p>
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25 pages, 2070 KiB  
Systematic Review
The Diagnostic Accuracy of Colon Capsule Endoscopy in Inflammatory Bowel Disease—A Systematic Review and Meta-Analysis
by Ian Io Lei, Camilla Thorndal, Muhammad Shoaib Manzoor, Nicholas Parsons, Charlie Noble, Cristiana Huhulea, Anastasios Koulaouzidis and Ramesh P. Arasaradnam
Diagnostics 2024, 14(18), 2056; https://doi.org/10.3390/diagnostics14182056 - 16 Sep 2024
Viewed by 213
Abstract
Colon capsule endoscopy (CCE) has regained popularity for lower gastrointestinal investigations since the COVID-19 pandemic. While there have been systematic reviews and meta-analyses on colonic polyp detection using CCE, there is a lack of comprehensive evidence concerning colonic inflammation. Therefore, this systematic review [...] Read more.
Colon capsule endoscopy (CCE) has regained popularity for lower gastrointestinal investigations since the COVID-19 pandemic. While there have been systematic reviews and meta-analyses on colonic polyp detection using CCE, there is a lack of comprehensive evidence concerning colonic inflammation. Therefore, this systematic review and meta-analysis aimed to assess the diagnostic accuracy of CCE for colonic inflammation, predominantly ulcerative colitis (UC) and Crohn’s disease (CD). Methods: We systematically searched electronic databases (EMBASE, MEDLINE, PubMed Central, and Cochrane Library) for studies comparing the diagnostic accuracy between CCE and optical endoscopy as the standard reference. A bivariate random effect model was used for the meta-analysis. Results: From 3797 publications, 23 studies involving 1353 patients were included. Nine studies focused on UC, and ten focused on CD. For UC, CCE showed a pooled sensitivity of 92% (95% CI, 88–95%), a specificity of 71% (95% CI, 35–92%), and an AUC of 0.93 (95% CI, 0.89–0.97). For CD, the pooled sensitivity was 92% (95% CI, 89–95%), and the specificity was 88% (95% CI, 84–92%), with an AUC of 0.87 (95% CI, 0.76–0.98). Overall, for inflammatory bowel disease, the pooled sensitivity, specificity, and AUC were 90% (95% CI, 85–93%), 76% (95% CI, 56–90%), and 0.92 (95% CI, 0.94–0.97), respectively. Conclusions: Despite the challenges around standardised disease scoring and the lack of histological confirmation, CCE performs well in diagnosing inflammatory bowel disease. It demonstrates high sensitivity in both UC and Crohn’s terminal ileitis and colitis and high specificity in Crohn’s disease. Further studies are needed to evaluate the diagnostic accuracy of other colonic inflammatory conditions. Full article
(This article belongs to the Special Issue Inflammatory Pathologies)
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<p>PRISMA flow chart [<a href="#B1-diagnostics-14-02056" class="html-bibr">1</a>].</p>
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<p>The forest plot of sensitivity (left) and specificity (right) of IBD (including both UC and CD disease activity) detection using CCE. Leighton 2017 [<a href="#B46-diagnostics-14-02056" class="html-bibr">46</a>], Ye C. A. 2013 [<a href="#B28-diagnostics-14-02056" class="html-bibr">28</a>], Juan-Acosta 2014 [<a href="#B29-diagnostics-14-02056" class="html-bibr">29</a>], Shi 2017 [<a href="#B30-diagnostics-14-02056" class="html-bibr">30</a>], Adler 2019 [<a href="#B31-diagnostics-14-02056" class="html-bibr">31</a>], Oliva 2014 [<a href="#B32-diagnostics-14-02056" class="html-bibr">32</a>] Sung 2012 [<a href="#B33-diagnostics-14-02056" class="html-bibr">33</a>], Meister 2013 [<a href="#B34-diagnostics-14-02056" class="html-bibr">34</a>], Hosoe 2013 [<a href="#B35-diagnostics-14-02056" class="html-bibr">35</a>], Hosoe 2018 [<a href="#B36-diagnostics-14-02056" class="html-bibr">36</a>], Oliva 2016 [<a href="#B37-diagnostics-14-02056" class="html-bibr">37</a>], Brodersen 2022 [<a href="#B38-diagnostics-14-02056" class="html-bibr">38</a>], Hausmann 2017 [<a href="#B39-diagnostics-14-02056" class="html-bibr">39</a>], Bruining 2020 [<a href="#B40-diagnostics-14-02056" class="html-bibr">40</a>], Yamada 2021 [<a href="#B41-diagnostics-14-02056" class="html-bibr">41</a>], Papalia 2021 [<a href="#B42-diagnostics-14-02056" class="html-bibr">42</a>], Brodersen 2023 [<a href="#B43-diagnostics-14-02056" class="html-bibr">43</a>], Hall 2015 [<a href="#B47-diagnostics-14-02056" class="html-bibr">47</a>], D’Haens 2015 [<a href="#B44-diagnostics-14-02056" class="html-bibr">44</a>].</p>
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<p>Summary receiver operating characteristic (sROC) curves of CCE for the diagnosis of (<b>a</b>) IBD overall, (<b>b</b>) ulcerative colitis, and (<b>c</b>) Crohn’s disease utilising the generalised linear mixed model (GLMM) from the “glmer” function in the R package “lme4”.</p>
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<p>Risk-of-bias assessment using the QUADAS 2 and QUADAS-C tools. Leighton 2017 [<a href="#B46-diagnostics-14-02056" class="html-bibr">46</a>], Ye 2013 [<a href="#B28-diagnostics-14-02056" class="html-bibr">28</a>], Juan-Acosta 2014 [<a href="#B29-diagnostics-14-02056" class="html-bibr">29</a>], Shi 2017 [<a href="#B30-diagnostics-14-02056" class="html-bibr">30</a>], Adler 2019 [<a href="#B31-diagnostics-14-02056" class="html-bibr">31</a>], Oliva 2014 [<a href="#B32-diagnostics-14-02056" class="html-bibr">32</a>] Sung 2012 [<a href="#B33-diagnostics-14-02056" class="html-bibr">33</a>], Meister 2013 [<a href="#B34-diagnostics-14-02056" class="html-bibr">34</a>], Oliva 2016 [<a href="#B37-diagnostics-14-02056" class="html-bibr">37</a>], Brodersen 2022 [<a href="#B38-diagnostics-14-02056" class="html-bibr">38</a>], Hausmann 2017 [<a href="#B39-diagnostics-14-02056" class="html-bibr">39</a>], Bruining 2020 [<a href="#B40-diagnostics-14-02056" class="html-bibr">40</a>], Yamada 2021 [<a href="#B41-diagnostics-14-02056" class="html-bibr">41</a>], D’Haens 2015 [<a href="#B44-diagnostics-14-02056" class="html-bibr">44</a>], Ismail 2021 [<a href="#B53-diagnostics-14-02056" class="html-bibr">53</a>], Akyuz 2016 [<a href="#B54-diagnostics-14-02056" class="html-bibr">54</a>], Eliakim 2006 [<a href="#B55-diagnostics-14-02056" class="html-bibr">55</a>], Herrerias-Gutierrez 2011 [<a href="#B56-diagnostics-14-02056" class="html-bibr">56</a>].</p>
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<p>Funnel plot for diagnostic odds ratios—Deeks’ regression test for publication bias. Test result: t = −1.26; df = 11; <span class="html-italic">p</span>-value = 0.2329. Bias estimate: −6.4309 (standard error = 5.0937); multiplicative residual heterogeneity variance (tau<sup>2</sup> = 66.0431).</p>
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<p>Scatterplots showing variations in the cut-off points as well as the accuracy of CCE in overall IBD diagnosis.</p>
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16 pages, 2430 KiB  
Article
Effect of Freeze–Thawing Treatment on Platelet-Rich Plasma Purified with Different Kits
by Ryoka Uchiyama, Haruka Omura, Miki Maehara, Eriko Toyoda, Miyu Tamaki, Makoto Ogawa, Tatsumi Tanaka, Masahiko Watanabe and Masato Sato
Int. J. Mol. Sci. 2024, 25(18), 9981; https://doi.org/10.3390/ijms25189981 (registering DOI) - 16 Sep 2024
Viewed by 381
Abstract
Osteoarthritis of the knee (OAK), a progressive degenerative disease affecting quality of life, is characterized by cartilage degeneration, synovial inflammation, and osteophyte formation causing pain and disability. Platelet-rich plasma (PRP) is an autologous blood product effective in reducing OAK-associated pain. PRP compositions depend [...] Read more.
Osteoarthritis of the knee (OAK), a progressive degenerative disease affecting quality of life, is characterized by cartilage degeneration, synovial inflammation, and osteophyte formation causing pain and disability. Platelet-rich plasma (PRP) is an autologous blood product effective in reducing OAK-associated pain. PRP compositions depend on their purification. In clinical practice, PRP is typically administered immediately after purification, while cryopreserved PRP is used in research. Platelets are activated by freezing followed by release of their humoral factors. Therefore, PRP without any manipulation after purification (utPRP) and freeze–thawed PRP (fPRP) may differ in their properties. We purified leukocyte-poor PRP (LPPRP) and autologous protein solution (APS) to compare the properties of utPRPs and fPRPs and their effects on OAK target cells. We found significant differences in platelet activation and humoral factor content between utPRPs and fPRPs in both LPPRP and APS. Freeze–thawing affected the anti-inflammatory properties of LPPRP and APS in chondrocytes and synovial cells differed. Both utPRPs and fPRPs inhibited polarization toward M1 macrophages while promoting polarization toward M2 macrophages. Freeze–thawing specifically affected humoral factor production in macrophages, suggesting that evaluating the efficacy of PRPs requires considering PRP purification methods, properties, and conditions. Understanding these variations may enhance therapeutic application of PRPs in OAK. Full article
(This article belongs to the Section Molecular Pharmacology)
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<p>(<b>A</b>) Flow cytometric analysis of platelet activation markers. (<b>B</b>,<b>C</b>) The positivity rates of CD40L (<b>B</b>) and CD62P (<b>C</b>) in platelets contained in LPPRP. (<b>D</b>,<b>E</b>) The positivity rates of CD40L (<b>D</b>) and CD62P (<b>E</b>) in platelets contained in APS. WB = whole blood, 1st = after first centrifugation, utPRP = PRP without any manipulation. Data are presented as the mean ± SEM. * <span class="html-italic">p</span> &lt; 0.05, ** <span class="html-italic">p</span> &lt; 0.01.</p>
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<p>Effect of PRPs on gene expression and humoral factor production of inflammatory cytokines and matrix metalloproteinases in synovial cells. (<b>A</b>,<b>C</b>) Gene expression of inflammatory cytokines (i.e., IL6, IL12, TNFα) and MMPs (i.e., MMP3, MMP13) in synovial cells treated with LPPRP (<b>A</b>) and APS (<b>C</b>). (<b>B</b>,<b>D</b>) Humoral factor concentration in culture media of synovial cells treated with LPPRP (<b>B</b>) and APS (<b>D</b>), normalized by CellTiter-Glo<sup>®</sup> assay. Mean ± SEM are indicated. Control group = IL1β-stimulated cells. * <span class="html-italic">p</span> &lt; 0.05, ** <span class="html-italic">p</span> &lt; 0.01 by one-way analyses of variance (ANOVA). Control group (<span class="html-italic">n</span> = 5): 5 synovial cells donors, PRP group (<span class="html-italic">n</span> = 30): 5 synovial cells donors, 6 PRP donors per group.</p>
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<p>Effect of PRPs on gene expression and humoral factor production of inflammatory cytokines and matrix metalloproteinases in chondrocytes. (<b>A</b>,<b>B</b>,<b>D</b>,<b>E</b>) Gene expression of inflammatory cytokines (i.e., IL6, IL12, TNFα), MMPs (i.e., MMP3, MMP13), and cartilage-related genes in chondrocytes treated with LPPRP (<b>A</b>,<b>B</b>) and APS (<b>D</b>,<b>E</b>). (<b>C</b>,<b>F</b>) Humoral factor concentration in culture media of chondrocytes treated with LPPRP (<b>C</b>) and APS (<b>F</b>), normalized by CellTiter-Glo<sup>®</sup> assay. Mean ± SEM are indicated. Control group = IL-1β-stimulated cells. * <span class="html-italic">p</span> &lt; 0.05, ** <span class="html-italic">p</span> &lt; 0.01 by one-way ANOVA. Control group (<span class="html-italic">n</span> = 5): 5 chondrocyte donors, PRP group (<span class="html-italic">n</span> = 30): 5 chondrocyte donors, 6 PRP donors per group.</p>
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<p>Effect of PRPs on macrophage polarization. (<b>A</b>) A histogram representation of typical flow cytometry results analyzing macrophage phenotype. Gray and dashed lines: isotype control; blue and solid lines: signals for each antibody. Mean fluorescence intensity (MFI) values of each antibody were used to calculate ΔMFI values: ΔMFI = MFI Sample–MFI Isotype. (<b>B</b>,<b>D</b>) Surface levels of CD80, CD86 (i.e., M1-associated markers), CD163, and CD206 (i.e., M2-associated markers) on MDM after treatment with LPPRP (<b>B</b>) and APS (<b>D</b>). (<b>C</b>,<b>E</b>) Humoral factor concentration in culture media after treatment with LPPRP (<b>C</b>) and APS (<b>E</b>), normalized by CellTiter-Glo<sup>®</sup> assay. Mean ± SEM are indicated. Control group = MDM. * <span class="html-italic">p</span> &lt; 0.05, ** <span class="html-italic">p</span> &lt; 0.01 by one-way ANOVA. Control group (<span class="html-italic">n</span> = 5): 5 monocyte donors, PRP group (<span class="html-italic">n</span> = 30): 5 monocyte donors, 6 PRP donors per group.</p>
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<p>Effect of PRPs on M1 macrophage polarization. (<b>A</b>,<b>C</b>) Surface levels of CD80, CD86 (i.e., M1-associated markers), CD163, and CD206 (i.e., M2-associated markers) on M1 macrophages after treatment with LPPRP (<b>A</b>) and APS (<b>C</b>). (<b>B</b>,<b>D</b>) Humoral factor concentration in culture media after treatment with LPPRP (<b>B</b>) and APS (<b>D</b>), normalized by CellTiter-Glo<sup>®</sup> assay. Mean ± SEM are indicated. Control group = M1. * <span class="html-italic">p</span> &lt; 0.05 by one-way ANOVA. Control group (<span class="html-italic">n</span> = 5): 5 monocyte donors, PRP group (<span class="html-italic">n</span> = 30): 5 monocyte donors, 6 PRP donors per group.</p>
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17 pages, 2921 KiB  
Article
Assessing the Anti-Inflammatory and Antioxidant Activity of Mangiferin in Murine Model for Myocarditis: Perspectives and Challenges
by Alexandra Popa, Lia-Oxana Usatiuc, Iuliu Calin Scurtu, Raluca Murariu, Alexandra Cofaru, Romelia Pop, Flaviu Alexandru Tabaran, Luciana Madalina Gherman, Dan Valean, Alexandru Cristian Bolundut, Rares Ilie Orzan, Ximena Maria Muresan, Andreea Georgiana Morohoschi, Sanda Andrei, Cecilia Lazea and Lucia Agoston-Coldea
Int. J. Mol. Sci. 2024, 25(18), 9970; https://doi.org/10.3390/ijms25189970 (registering DOI) - 16 Sep 2024
Viewed by 285
Abstract
Myocarditis is a major cause of heart failure and death, particularly in young individuals. Current treatments are mainly symptomatic, but emerging therapies focus on targeting inflammation and fibrosis pathways. Natural bioactive compounds like flavonoids and phenolic acids show promising anti-inflammatory and antioxidant properties. [...] Read more.
Myocarditis is a major cause of heart failure and death, particularly in young individuals. Current treatments are mainly symptomatic, but emerging therapies focus on targeting inflammation and fibrosis pathways. Natural bioactive compounds like flavonoids and phenolic acids show promising anti-inflammatory and antioxidant properties. Corticosteroids are frequently employed in the treatment of autoimmune myocarditis and appear to lower mortality rates compared to conventional therapies for heart failure. This study aims to explore the effects of Mangiferin on pro-inflammatory cytokine levels, nitro-oxidative stress markers, histopathological alterations, and cardiac function in experimental myosin-induced autoimmune myocarditis. The effects were compared to Prednisone, used as a reference anti-inflammatory compound, and Trolox, used as a reference antioxidant. The study involved 30 male Wistar–Bratislava rats, which were randomly divided into five groups: a negative control group (C−), a positive control group with induced myocarditis using a porcine myosin solution (C+), three groups with induced myocarditis receiving Mangiferin (M), Prednisone (P), or Trolox (T) as treatment. Cardiac function was evaluated using echocardiography. Biochemical measurements of nitro-oxidative stress and inflammatory markers were conducted. Finally, histopathological changes were assessed. At echocardiography, the evaluation of the untreated myocarditis group showed a trend toward decreased left ventricular ejection fraction (LVEF) but was not statistically significant, while all treated groups showed some improvement in LVEF and left ventricular fraction shortening (LVFS). Significant changes were seen in the Mangiferin group, with lower end-diastolic left ventricular posterior wall (LVPWd) by day 21 compared to the Trolox group (p < 0.001). In the first week of the experiment, levels of interleukins (IL)-1β, IL-6, and tumour necrosis factor (TNF)-α were significantly higher in the myosin group compared to the negative control group (p < 0.001, p < 0.001, p < 0.01), indicating the progression of inflammation in this group. Treatment with Mangiferin, Prednisone, and Trolox caused a significant reduction in IL-1β compared to the positive control group (p < 0.001). Notably, Mangiferin resulted in a superior reduction in IL-1β compared to Prednisone (p < 0.05) and Trolox (p < 0.05). Furthermore, Mangiferin treatment led to a statistically significant increase in total oxidative capacity (TAC) (p < 0.001) and a significant reduction in nitric oxide (NOx) levels (p < 0.001) compared to the negative control group. Furthermore, when compared to the Prednisone-treated group, Mangiferin significantly reduced NOx levels (p < 0.001) and increased TAC levels (p < 0.001). Mangiferin treatment significantly lowered creatine kinase (CK) and aspartate aminotransferase (AST) levels on day 7 (p < 0.001 and p < 0.01, respectively) and reduced CK levels on day 21 (p < 0.01) compared to the untreated group. In the nontreated group, the histological findings at the end of the experiment were consistent with myocarditis. In the group treated with Mangiferin, only one case exhibited mild inflammatory infiltrates, represented by mononucleated leukocytes admixed with few neutrophils, with the severity graded as mild. Statistically significant correlations between the grades (0 vs. 1–2) and the study groups have been highlighted (p < 0.005). This study demonstrated Mangiferin’s cardioprotective effects in autoimmune myocarditis, showing reduced oxidative stress and inflammation. Mangiferin appears promising as a treatment for acute myocarditis, but further research is needed to compare its efficacy with other treatments like Trolox and Prednisone. Full article
(This article belongs to the Special Issue Bioactive Compounds in the Prevention of Chronic Diseases)
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<p>A proposed schematic representation of the progression from inflammation to fibrosis in heart tissue following exposure to an external pathogen. Dendritic cells recognize the pathogen, triggering the activation of the nuclear factor (NF)-κB/p50 signaling pathway, leading to the expression of type I interferon (IFN-α/β) genes. This interaction further activates T helper (Th) cells, with Th1 promoting inflammation via cytokines such as IFN-γ and Th2, mediating anti-inflammatory responses through interleukin (IL)-6, IL-23, transforming growth factor (TGF)-β, and Th17, contributing to chronic inflammation and fibrosis. Macrophages also amplify the inflammatory response through cytokine release. Mangiferin inhibits the NF-κB pathway, thereby reducing immune cell activation. Trolox reduces oxidative stress by decreasing reactive oxygen species (ROS) and preventing apoptosis, while Prednisone is used to decrease inflammation. Additionally, the activation of receptor tyrosine kinases (RTKs) initiates the PI3K/Akt pathway, driving cell growth, proliferation, and angiogenesis, ultimately leading to tissue remodeling and fibrosis.</p>
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<p>A representative echocardiographic image (parasternal short axis view at the level of the papillary muscles) showing the measurements taken on day two from a subject in the Mangiferin group for illustrative purposes.</p>
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<p>Echocardiographic evaluation of left ventricular function in EAM rats. (<b>A</b>). Interventricular septum systolic thickness (IVSs); (<b>B</b>). left ventricular posterior wall diastolic thickness (LVPWd); (<b>C</b>). left ventricular diastolic diameter (LVDd); (<b>D</b>). left ventricular systolic diameter (LVDs); (<b>E</b>). left ventricular ejection fraction (LVEF); (<b>F</b>). left ventricular fractional shortening (LVFS). * Significance vs. C− group for the corresponding day, <span class="html-italic">p</span> &lt; 0.05; ** significance vs. C− group for the corresponding day, <span class="html-italic">p</span> &lt; 0.01; # significance vs. C+ group for the corresponding day, <span class="html-italic">p</span> &lt; 0.05; ## significance vs. C+ group for the corresponding day, <span class="html-italic">p</span> &lt; 0.01; <span>$</span> significance vs. T group for the corresponding day, <span class="html-italic">p</span> &lt; 0.05; <span>$</span><span>$</span> significance vs. T group for the corresponding day, <span class="html-italic">p</span> &lt; 0.01; <span>$</span><span>$</span><span>$</span> significance vs. T group for the corresponding day, <span class="html-italic">p</span> &lt; 0.001; §§ day 2 vs. day 21 for the corresponding group, <span class="html-italic">p</span> &lt; 0.01.</p>
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<p>Incidence of myocarditis-suggestive lesions compared across the studied groups and the severity score assessement. C−: negative control group, C+: positive control group with myocarditis induced, M: myocarditis group treated with Mangiferin, P: myocarditis group treated with Prednisone, T: myocarditis group treated with Trolox.</p>
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<p>Histopathological images of myocardial tissue. (<b>A</b>–<b>C</b>) Negative control group—no significant findings are observed. (<b>D</b>–<b>F</b>) Positive control group with induced myocarditis (without treatment)—showing multifocal inflammatory infiltrate consisting of mononuclear leukocytes (black arrows), a few neutrophils (red arrows), and focal fibrosis ((<b>F</b>), indicated by the arrow). (<b>G</b>–<b>I</b>) Mangiferin-treated group—in one individual, there is focal inflammatory infiltrate consisting of mononuclear leukocytes (black arrows) with a few neutrophils (red arrows). Significant fibrosis is absent. (<b>J</b>–<b>L</b>) Prednisone-treated group—no significant findings observed. (<b>M</b>–<b>O</b>) Trolox-treated group—no significant findings observed. H&amp;E stain, Obx20: images (<b>A</b>,<b>D</b>,<b>G</b>,<b>J</b>,<b>M</b>); Obx100: images (<b>B</b>,<b>E</b>,<b>H</b>,<b>K</b>,<b>N</b>); TM stain, Obx20: images (<b>C</b>,<b>F</b>,<b>I</b>,<b>L</b>,<b>O</b>).</p>
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<p>Distribution of the experimental groups, treatments, and investigations. The negative control group (C−) received a subcutaneous injection of 1 mL of 0.9% saline solution. Myocarditis was induced through porcine myosine administration on days 0 and 7 in the C+, M, P, and T groups by subcutaneous administration of 0.25 mg/100 g body weight of myosin solution (0.05 mL). The M group was treated with Mangiferin (2.5 mg/100 g body weight), the P group received Prednisone (0.25 mg/100 g body weight), and the T group was administered Trolox (20 mg/100 g body weight). The treatments were given via gavage from day 2 to day 21. Echocardiography was performed on days 2 and 21, and blood samples were collected on days 2, 7, and 21.</p>
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11 pages, 715 KiB  
Article
Effect of Neutrophil–Platelet Interactions on Cytokine-Modulated Expression of Neutrophil CD11b/CD18 (Mac-1) Integrin Complex and CCR5 Chemokine Receptor in Stable Coronary Artery Disease: A Sub-Study of SMARTool H2020 European Project
by Silverio Sbrana, Stefano Salvadori, Rosetta Ragusa, Elisa Ceccherini, Adrian Florentin Suman, Antonella Cecchettini, Chiara Caselli, Danilo Neglia, Gualtiero Pelosi and Silvia Rocchiccioli
Hearts 2024, 5(3), 410-420; https://doi.org/10.3390/hearts5030029 (registering DOI) - 16 Sep 2024
Viewed by 185
Abstract
Atherosclerosis is an inflammatory disease wherein neutrophils play a key role in plaque evolution. We observed that neutrophil CD11b was associated with a higher necrotic core volume in coronary plaques. Since platelets modulate neutrophil function, we explored the influence of neutrophil–platelet conjugates on [...] Read more.
Atherosclerosis is an inflammatory disease wherein neutrophils play a key role in plaque evolution. We observed that neutrophil CD11b was associated with a higher necrotic core volume in coronary plaques. Since platelets modulate neutrophil function, we explored the influence of neutrophil–platelet conjugates on the cytokine-modulated neutrophil complex CD11b/CD18 and CCR5 receptor expression. In 55 patients [68.53 ± 7.95 years old (mean ± SD); 71% male], neutrophil positivity for CD11b, CD18 and CCR5 was expressed as Relative Fluorescence Intensity (RFI) and taken as a dependent variable. Cytokines and chemokines were assessed by ELISA. Following log-10-based logarithmic transformation, they were used as independent variables in Model 1 of multiple regression together with Body Mass Index and albumin. Model 1 was expanded with the RFI of neutrophil CD41a+ (model 2). The RFI of neutrophil CD41a+ correlated positively and significantly with CD11b, CD18, and CCR5. In Model 2, CCR5 correlated positively only with the RFI of neutrophil CD41a+. Albumin maintained its positive effect on CD11b in both models. These observations indicate the complexity of neutrophil phenotypic modulation in stable CAD. Despite limitations, these findings suggest there is a role played by neutrophil–platelet interaction on the neutrophil cytokine-modulated expression of adhesive and chemotactic receptors. Full article
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<p>Representative example of flow cytometry quantification of complexes neutrophil-CD41a+ (NPAs, neutrophil–platelet aggregates). (<b>A</b>) Neutrophil cluster identification (region R1) based on its low CD14 expression (FL3) and side-scattering (SSC) morphological characteristics. (<b>B</b>) The R1-based histogram’s subtraction analysis [positive events (continuous line) minus isotype control (dotted line)] was used to quantify both the percentage of complexes CD41a+ (percentage of events in M1 marker) and their RFI (median of M1 gray histogram minus median of the isotype control).</p>
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<p>Schematic representation of the main soluble effector molecules involved in the platelet-mediated modulation model of circulating neutrophil phenotypes proposed in our study.</p>
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13 pages, 600 KiB  
Article
The Effectiveness of Individualized Oral Hygiene Education in Preventing Dental Diseases: A Clinical Study
by Fanni Simon, Gyula Szabó, Mercédesz Orsós, Eitan Mijiritsky and Orsolya Németh
J. Clin. Med. 2024, 13(18), 5481; https://doi.org/10.3390/jcm13185481 - 15 Sep 2024
Viewed by 331
Abstract
Background: Without mechanical cleaning, gingivitis can develop within three weeks. The first clinical sign is bleeding on positive probing. The accumulation of dental biofilm triggers an inflammatory gingival response. In the past decade, attention has focused mainly on interproximal areas and the [...] Read more.
Background: Without mechanical cleaning, gingivitis can develop within three weeks. The first clinical sign is bleeding on positive probing. The accumulation of dental biofilm triggers an inflammatory gingival response. In the past decade, attention has focused mainly on interproximal areas and the use of customized interproximal toothbrushes. The aim of this study was to evaluate the effectiveness of individualized oral hygiene education and its role in dental disease prevention among patients with dental problems. Methods: Altogether, 102 patients, 38 males and 64 females, were included in the study. All patients were aged over 18 years. Before treatment, patients were clinically and radiologically examined, their full mouth plaque score (FMPS), full mouth bleeding score (FMBS), and bleeding on brushing (BOB) were recorded, and matrix-metalloproteinase-8 (MMP-8) was measured by using a chair-side MMP-8 measuring system. Patients in group A had gingivitis but no periodontal damage, and group B had periodontal damage. Patients in both groups were divided into four subgroups based on their toothbrushing habits and the oral health education they received. Three months after the initial examination, each patient was examined three more times (2, 4, and 12 weeks later). Results: It was concluded that subjects in groups A1 and B1 showed a significant reduction in BOB, MMP-8, FMBS, and FMPS levels after two weeks. Solo Prophylaxis (A1 and B1) remained a well-constructed protocol and caused the complete resolution of interdental inflammation after two weeks. Other subgroups achieved significant reductions only after 12 weeks. Conclusions: BOB and MMP-8 tests are valuable complements in preventive dentistry, and are able to detect potential pathological processes. The clinical relevance of BOB testing, in addition to FMBS, FMPS and gingival inflammation testing, can be demonstrated to patients, which may increase compliance. Full article
(This article belongs to the Special Issue Modern Patient-Centered Dental Care)
20 pages, 5074 KiB  
Article
Chlorogenic Acid Enhances the Intestinal Health of Weaned Piglets by Inhibiting the TLR4/NF-κB Pathway and Activating the Nrf2 Pathway
by Beibei Zhang, Min Tian, Jing Wu, Yueqin Qiu, Xiaoming Xu, Chaoyang Tian, Jing Hou, Li Wang, Kaiguo Gao, Xuefen Yang and Zongyong Jiang
Int. J. Mol. Sci. 2024, 25(18), 9954; https://doi.org/10.3390/ijms25189954 (registering DOI) - 15 Sep 2024
Viewed by 228
Abstract
Chlorogenic acid (CGA) is a natural polyphenol with potent antioxidant and anti-inflammatory activities. However, the exact role of it in regulating intestinal health under oxidative stress is not fully understood. This study aims to investigate the effects of dietary CGA supplementation on the [...] Read more.
Chlorogenic acid (CGA) is a natural polyphenol with potent antioxidant and anti-inflammatory activities. However, the exact role of it in regulating intestinal health under oxidative stress is not fully understood. This study aims to investigate the effects of dietary CGA supplementation on the intestinal health of weaned piglets under oxidative stress, and to explore its regulatory mechanism. Twenty-four piglets were randomly divided into two groups and fed either a basal diet (CON) or a basal diet supplemented with 200 mg/kg CGA (CGA). CGA reduced the diarrhea rate, increased the villus height in the jejunum, and decreased the crypt depth in the duodenum, jejunum, and ileum of the weaned piglets (p < 0.05). Moreover, CGA increased the protein abundance of Claudin-1, Occludin, and zonula occludens (ZO)-1 in the jejunum and ileum (p < 0.05). In addition, CGA increased the mRNA expression of pBD2 in the jejunum, and pBD1 and pBD2 in the ileum (p < 0.05). The results of 16S rRNA sequencing showed that CGA altered the ileal microbiota composition and increased the relative abundance of Lactobacillus reuteri and Lactobacillus pontis (p < 0.05). Consistently, the findings suggested that the enhancement of the intestinal barrier in piglets was associated with increased concentrations of T-AOC, IL-22, and sIgA in the serum and T-AOC, T-SOD, and sIgA in the jejunum, as well as T-AOC and CAT in the ileum caused by CGA (p < 0.05). Meanwhile, CGA decreased the concentrations of MDA, IL-1β, IL-6, and TNF-α in the serum and jejunum and IL-1β and IL-6 in the ileum (p < 0.05). Importantly, this study found that CGA alleviated intestinal inflammation and oxidative stress in the piglets by inhibiting the TLR4/NF-κB signaling pathway and activating the Nrf2 signaling pathway. These findings showed that CGA enhances the intestinal health of weaned piglets by inhibiting the TLR4/NF-κB pathway and activating the Nrf2 pathway. Full article
(This article belongs to the Special Issue Antibacterial and Antioxidant Effects of Plant-Sourced Compounds)
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<p>Effects of dietary supplementation with CGA on the villi height and crypt depth of the small intestine in piglets. (<b>A</b>) H&amp;E staining of the intestine (scale bar, 500 μm); (<b>B</b>–<b>D</b>) analysis of villi height and crypt depth in the intestine. Values are presented as the mean ± SEM (<span class="html-italic">n</span> = 6). *, 0.01 &lt; <span class="html-italic">p</span> ≤ 0.05. **, <span class="html-italic">p</span> ≤ 0.01.</p>
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<p>Effects of dietary CGA supplementation on the expression of tight junctions in the jejunum and ileum. (<b>A</b>,<b>B</b>) The immunoreactivity of tight junctions in the jejunum and ileum of piglets; (<b>C</b>–<b>F</b>) Western blot analysis of tight junctions in the jejunum and ileum of piglets. <span class="html-italic">n</span> = 6. *, 0.01 &lt; <span class="html-italic">p</span> ≤ 0.05. **, <span class="html-italic">p</span> ≤ 0.01.</p>
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<p>Effects of dietary CGA supplementation on the mRNA expression of mucins and porcine beta defensins in the jejunum (<b>A</b>) and ileum (<b>B</b>) mucosa of piglets. MUC, mucin; pBD, porcine beta defensins; PG1, Protegrin-1. Values are presented as the mean ± SEM (<span class="html-italic">n</span> = 6). *, 0.01 &lt; <span class="html-italic">p</span> ≤ 0.05.</p>
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<p>Effects of dietary CGA supplementation on the ileal microbiota of piglets. (<b>A</b>–<b>G</b>) Relative abundance of microbiota at the phylum, genus, and species levels. (<b>H</b>) Beta diversity; (<b>I</b>–<b>K</b>) alpha diversity. Values are presented as the mean ± SEM (<span class="html-italic">n</span> = 6). *, 0.01 &lt; <span class="html-italic">p</span> ≤ 0.05. **, <span class="html-italic">p</span> ≤ 0.01.</p>
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<p>Effects of dietary supplementation with CGA on antioxidant status and immune-inflammatory level in the serum of piglets. (<b>A</b>–<b>D</b>) The antioxidative and oxidative indicators in the serum. (<b>E</b>–<b>H</b>); the concentration of inflammatory factors in the serum; (<b>I</b>,<b>J</b>) the immunoglobulin concentration in the serum. Values are presented as the mean ± SEM (<span class="html-italic">n</span> = 6). *, 0.01 &lt; <span class="html-italic">p</span> ≤ 0.05. **, <span class="html-italic">p</span> ≤ 0.01.</p>
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<p>Effects of dietary supplementation with CGA on antioxidant status and immune-inflammatory level in the jejunum and ileum of piglets. (<b>A</b>–<b>D</b>) The antioxidative and oxidative indicators in the serum; (<b>E</b>–<b>H</b>) the concentration of inflammatory factors in the serum; (<b>I</b>) the immunoglobulin concentration in the serum. Values are presented as the mean ± SEM (<span class="html-italic">n</span> = 6). *, 0.01 &lt; <span class="html-italic">p</span> ≤ 0.05. **, <span class="html-italic">p</span> ≤ 0.01.</p>
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<p>Effects of dietary CGA supplementation on the activation of the NF-κB and Nrf2 signaling pathways in the jejunum and ileum of piglets. (<b>A</b>–<b>D</b>) Jejunum; (<b>E</b>–<b>H</b>) ileum. *, 0.01 &lt; <span class="html-italic">p</span> ≤ 0.05. **, <span class="html-italic">p</span> ≤ 0.01.</p>
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<p>Correlation analysis between microorganisms, oxidative stress indicators, immunoglobulins, and inflammatory factors in the intestines of piglets. *, 0.01 &lt; <span class="html-italic">p</span> ≤ 0.05. **, <span class="html-italic">p</span> ≤ 0.01.</p>
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<p>Network pharmacological analysis between CGA, oxidative stress, and inflammation. (<b>A</b>,<b>B</b>) Intersection analysis between CGA targets and the disease targets of oxidative stress and inflammation, as well as screening of core targets; (<b>C</b>) the schematic diagram of the interaction between CGA and TLR4; (<b>D</b>) the top 20 KEGG pathways.</p>
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12 pages, 881 KiB  
Review
From a Cup of Tea to Cardiovascular Care: Vascular Mechanisms of Action
by Marios Sagris, Panayotis K. Vlachakis, Spyridon Simantiris, Panagiotis Theofilis, Maria Gerogianni, Paschalis Karakasis, Konstantinos Tsioufis and Dimitris Tousoulis
Life 2024, 14(9), 1168; https://doi.org/10.3390/life14091168 - 15 Sep 2024
Viewed by 306
Abstract
Tea consumption is increasingly recognized for its potential benefits to cardiovascular health. This study reviews the available research, concentrating on the major components of tea and their mechanisms of action in the cardiovascular system. Tea is abundant in bioactive compounds, such as flavonoids [...] Read more.
Tea consumption is increasingly recognized for its potential benefits to cardiovascular health. This study reviews the available research, concentrating on the major components of tea and their mechanisms of action in the cardiovascular system. Tea is abundant in bioactive compounds, such as flavonoids and polysaccharides, which possess significant antioxidant and anti-inflammatory properties. These compounds play a crucial role in mitigating oxidative stress and inflammation, thereby supporting cardiovascular health. They enhance endothelial function, leading to improved vascular relaxation and reduced arterial stiffness, and exhibit antithrombotic effects. Additionally, regular tea consumption is potentially associated with better regulation of blood pressure, improved cholesterol profiles, and effective blood sugar control. It has been suggested that incorporating tea into daily dietary habits could be a practical strategy for cardiovascular disease prevention and management. Despite the promising evidence, more rigorous clinical trials are needed to establish standardized consumption recommendations and fully understand long-term effects. This review offers a more comprehensive analysis of the current evidence based on endothelium function and identifies the gaps that future research should address. Full article
(This article belongs to the Special Issue Diet and Vascular Disease)
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<p>Chemical components of tea and their influence on the endothelium.</p>
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<p>Tea targets in cardiovascular health. Created with <a href="https://www.biorender.com/" target="_blank">https://www.biorender.com/</a>.</p>
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14 pages, 12968 KiB  
Article
Melatonin and Bacterial Cellulose Regulate the Expression of Inflammatory Cytokines, VEGF, PCNA, and Collagen in Cutaneous Wound Healing in Diabetic Rats
by Jaiurte Gomes Martins da Silva, Ismaela Maria Ferreira de Melo, Érique Ricardo Alves, Glícia Maria de Oliveira, Anderson Arnaldo da Silva, Isabela Macário Ferro Cavalcanti, Diego Neves Araujo, Flávia Cristina Morone Pinto, José Lamartine de Andrade Aguiar, Valéria Wanderley Teixeira and Álvaro Aguiar Coelho Teixeira
Polymers 2024, 16(18), 2611; https://doi.org/10.3390/polym16182611 - 15 Sep 2024
Viewed by 347
Abstract
The poor healing of diabetic wounds is characterized by prolonged inflammation and decreased collagen deposition. Diabetic patients exhibit changes in the plasma concentrations of pro-inflammatory cytokines, and the role of specific dressings may have an impact on healing. This study aims to evaluate [...] Read more.
The poor healing of diabetic wounds is characterized by prolonged inflammation and decreased collagen deposition. Diabetic patients exhibit changes in the plasma concentrations of pro-inflammatory cytokines, and the role of specific dressings may have an impact on healing. This study aims to evaluate the effects of a combined treatment comprising a bacterial cellulose dressing and melatonin application on the regulation and expression of inflammatory cytokines, VEGF, PCNA, and collagen in the healing of cutaneous wounds of diabetic rats. Pro-inflammatory cytokines, including IL-6, TNF-α, and VEGF, along with PCNA and type I and III collagen, were evaluated after 14 days. Immunohistochemistry showed decreased levels of IL-6, TNF-α, and VEGF, along with an increased expression of PCNA and type I collagen, in the groups treated exclusively with melatonin and bacterial cellulose associated with melatonin compared to the control and the commercial healing agent. It was concluded that treating the skin lesions of diabetic animals supplemented with melatonin using a bacterial cellulose-based dressing has positive effects in regulating the expression of inflammatory cytokines, vascular endothelial growth factor, and collagen, showing that this association could be a viable therapy approach in wound healing. Full article
(This article belongs to the Special Issue Hydrogel Materials for Drug Delivery and Tissue Engineering)
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<p>Immunohistochemical analysis for IL-6 of wounds from animals at day 14. (<b>A</b>) GC group; (<b>B</b>) GCC group; (<b>C</b>) GDCB group; (<b>D</b>) GDMCB group. There is a higher expression in the GC and GDCC groups and a lower expression in the GDMCB group. (<b>E</b>) Quantification in pixels. Means with the same letter do not differ significantly from each other, as determined via Tukey and Kramer’s multiple comparisons test (<span class="html-italic">p</span> &gt; 0.05).</p>
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<p>Immunohistochemical analysis for TNFα of wounds from animals at day 14. (<b>A</b>) GC group; (<b>B</b>) GCC group; (<b>C</b>) GDCB group; (<b>D</b>) GDMCB group. There is a higher expression in the GC and GDCC groups and a lower expression in the GDMCB group. (<b>E</b>) Quantification in pixels. Means with the same letter do not differ significantly from each other, as determined via Tukey and Kramer’s multiple comparisons test (<span class="html-italic">p</span> &gt; 0.05).</p>
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<p>Immunohistochemical analysis for VEGF of wounds from animals at day 14. (<b>A</b>) GC group; (<b>B</b>) GCC group; (<b>C</b>) GDCB group; (<b>D</b>) GDMCB group. There is a higher expression in the GC and GDCC groups and a lower expression in the GDCB and GDMCB groups. (<b>E</b>) Quantification in pixels. Means followed by the same letter do not differ significantly from each other, as determined via Tukey and Kramer’s multiple comparisons test (<span class="html-italic">p</span> &gt; 0.05).</p>
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<p>Immunohistochemical analysis for PCNA of wounds from animals at day 14. (<b>A</b>) GC; (<b>B</b>) GCC; (<b>C</b>) GDCB; (<b>D</b>) GDMCB. There is a strong expression in the GC and GDCC groups and higher rates of proliferation in the GDCB and GDMCB groups. (<b>E</b>) Quantification in pixels. Means followed by the same letter do not differ significantly from each other, as determined via Tukey and Kramer’s multiple comparisons test (<span class="html-italic">p</span> &gt; 0.05).</p>
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<p>Quantification of collagen I and III of wounds from animals at day 14. There are higher rates of proliferation in the GDCB and GDMCB groups. Means followed by the same letter do not differ significantly from each other, as determined via Tukey and Kramer’s multiple comparisons test (<span class="html-italic">p</span> &gt; 0.05).</p>
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<p>Photomicrographs of the deposition and organization of collagen fibers in skin lesions from animals evaluated 14 days after diabetes induction and respective treatments. (<b>A</b>) GC; (<b>B</b>) GDCC; (<b>C</b>) GDCB; and (<b>D</b>) GDMCB. There is a higher concentration of type III collagen fibers (yellow green) in (<b>A</b>,<b>B</b>) and a higher concentration of type I collagen fibers (red) in (<b>C</b>,<b>D</b>). For staining, Picrosirius Red was used, and visualization was carried out via polarized light microscopy.</p>
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