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Search Results (1,311)

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13 pages, 2447 KiB  
Article
Gaining Insight into Mitochondrial Targeting: AUTAC-Biguanide as an Anticancer Agent
by Julie Vatté, Véronique Bourdeau, Gerardo Ferbeyre and Andreea R. Schmitzer
Molecules 2024, 29(16), 3773; https://doi.org/10.3390/molecules29163773 - 9 Aug 2024
Viewed by 158
Abstract
AUTAC-Biguanide is a hybrid compound designed to target mitochondria, inducing their degradation by mitophagy. This study unveils the potential of biguanides as cancer cell-targeting agents, emphasizing AUTAC-Biguanide’s superior antiproliferative properties compared to metformin and its selectivity for cancer cells. The mechanism behind this [...] Read more.
AUTAC-Biguanide is a hybrid compound designed to target mitochondria, inducing their degradation by mitophagy. This study unveils the potential of biguanides as cancer cell-targeting agents, emphasizing AUTAC-Biguanide’s superior antiproliferative properties compared to metformin and its selectivity for cancer cells. The mechanism behind this heightened effect includes the ability of AUTAC-Biguanide to trigger mitophagy. By providing a comprehensive analysis of these findings, this study adds valuable insights to the field of mitochondrial-targeting anticancer agents. Full article
(This article belongs to the Section Chemical Biology)
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<p>Design and mechanism of AUTAC-Biguanide. (<b>A</b>) Mode of action of the AUTAC compound and the mechanism of autophagy. (<b>B</b>) S-guanylation and ubiquitination protein recognition mode for selective degradation by autophagy. (<b>C</b>) Design and structure of AUTAC-Biguanide.</p>
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<p>Study of the effect of AUTAC-Biguanide <b>6</b> on different cell lines. (<b>A</b>) Effect of <b>6</b> on pancreatic cancer cells KP4 compared to metformin (<b>B</b>) Effect of <b>6</b> on the proliferation and growth of KP4 and PANC1 (cancer cells), and hTERT-HPNE and IMR90 (healthy cells), to assess its selectivity for cancer cells versus healthy cells.</p>
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<p>Confocal microscopy images of KP4 pancreatic cancer cells following treatment with AUTAC-Biguanide <b>6</b> or controls. (<b>A</b>) Morphology of KP4 cells after 24 h of treatment with DMSO, metformin (2 mM), compounds <b>7</b> (1 mM), or <b>6</b> (50 μM, 100 μM, and 200 μM), and staining of mitochondria with the Mitotracker<sup>®</sup> Deep Red FM (MTDR) fluorescent probe and the nuclei with the fluorescent dye DAPI; cell morphology counts performed on a minimum of 100 cells per treatment (n &gt; 2). (<b>B</b>) Observation of KP4 cells after 24 h of treatment with DMSO, metformin (2 mM), or compound <b>6</b> (200 μM) by immunofluorescence of the TOMM20 protein performed with the combination of antibodies against TOMM20 and an anti-mouse Alexa Fluor 488. The nuclei were stained with the fluorescent dye DAPI. Scale bars: 10 µm.</p>
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<p>Effect of AUTAC-Biguanide <b>6</b> and its controls on OXPHOS proteins levels in KP4 after 24 h of treatment and relative quantification of protein levels for metformin and AUTAC-Biguanide (<b>6</b>); * <span class="html-italic">p</span> ≤ 0.05; ** <span class="html-italic">p</span> ≤ 0.01 (ANOVA).</p>
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<p>Effect of AUTAC-Biguanide <b>6</b> and its controls on LC3-I and LC3-II protein levels. (<b>A</b>) Immunoblot for the study of LC3-I and LC3-II protein levels in KP4 after 24 h of treatment and relative quantification of protein levels for metformin (Met.), AUTAC-Hexyl (<b>7</b>), and AUTAC-Biguanide (<b>6</b>); * <span class="html-italic">p</span> ≤ 0.05; ** <span class="html-italic">p</span> ≤ 0.001 (ANOVA). (<b>B</b>) Effect of AUTAC-Biguanide <b>6</b> and its controls on LC3-I and LC3-II protein levels in the absence and presence of chloroquine; immunoblot for the study of LC3-I and LC3-II protein levels in KP4, with and without chloroquine, after 24 h of treatment and relative quantification of protein levels for metformin, <b>7</b> and <b>6</b>; * <span class="html-italic">p</span> ≤ 0.01; ** <span class="html-italic">p</span> ≤ 0.001 (ANOVA).</p>
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<p>Synthesis of AUTAC-Biguanide and its control, AUTAC-Hexyl. (<b>A</b>) Synthesis of intermediate <b>1</b>. (<b>B</b>) Synthesis of AUTAC-Biguanide <b>6</b>. (<b>C</b>) Synthesis of AUTAC-Hexyl <b>7</b>.</p>
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18 pages, 1606 KiB  
Review
mTOR Dysregulation, Insulin Resistance, and Hypertension
by Silviu Marcel Stanciu, Mariana Jinga, Daniela Miricescu, Constantin Stefani, Remus Iulian Nica, Iulia-Ioana Stanescu-Spinu, Ileana Adela Vacaroiu, Maria Greabu and Silvia Nica
Biomedicines 2024, 12(8), 1802; https://doi.org/10.3390/biomedicines12081802 - 8 Aug 2024
Viewed by 254
Abstract
Worldwide, diabetes mellitus (DM) and cardiovascular diseases (CVDs) represent serious health problems associated with unhealthy diet and sedentarism. Metabolic syndrome (MetS) is characterized by obesity, dyslipidemia, hyperglycemia, insulin resistance (IR) and hypertension. The mammalian target of rapamycin (mTOR) is a serine/threonine kinase with [...] Read more.
Worldwide, diabetes mellitus (DM) and cardiovascular diseases (CVDs) represent serious health problems associated with unhealthy diet and sedentarism. Metabolic syndrome (MetS) is characterized by obesity, dyslipidemia, hyperglycemia, insulin resistance (IR) and hypertension. The mammalian target of rapamycin (mTOR) is a serine/threonine kinase with key roles in glucose and lipid metabolism, cell growth, survival and proliferation. mTOR hyperactivation disturbs glucose metabolism, leading to hyperglycemia and further to IR, with a higher incidence in the Western population. Metformin is one of the most used hypoglycemic drugs, with anti-inflammatory, antioxidant and antitumoral properties, having also the capacity to inhibit mTOR. mTOR inhibitors such as rapamycin and its analogs everolimus and temsirolimus block mTOR activity, decrease the levels of glucose and triglycerides, and reduce body weight. The link between mTOR dysregulation, IR, hypertension and mTOR inhibitors has not been fully described. Therefore, the main aim of this narrative review is to present the mechanism by which nutrients, proinflammatory cytokines, increased salt intake and renin–angiotensin–aldosterone system (RAAS) dysregulation induce mTOR overactivation, associated further with IR and hypertension development, and also mTOR inhibitors with higher potential to block the activity of this protein kinase. Full article
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<p>Phosphatidylinositol 3-kinase (PI3K) protein kinases B (AKT)/mammalian target of rapamycin (mTOR) pathway in healthy conditions: Nutrients, growth factors, cytokines and insulin bind to tyrosine kinases receptors (RTKs), leading to insulin receptors substrate 1 or 2 (IRS1/IRS2) activation and further AKT activation by phosphorylation. Once activated, AKT will phosphorylate other protein kinases such as mTOR, composed of the two complexes mTOR complex 1 (mTORC1) and mTOR complex 2 (mTORC2). mTORC1 activates sterol response element binding protein (SREBP) and eukaryotic translation initiator factor 4E binding protein (4EBP) and 70Ka ribosomal protein S56 kinase 1 (p70S6K1), leading to lipid and protein synthesis, respectively. mTORC1 inhibits the activity of unc-51-like kinase 1 (ULK1) and autophagy-related gene 13 (ATG13) blocking autophagy. Inactivation of AKT substrate 160 (AS160) and glycogen synthase 3 (GSK3) induces plasma membrane GLUT translocation. mTORC2 activates other protein kinases such as A, G and C, which positively regulate cellular metabolism. Activation of PI3K/AKT/mTOR will be correlated with cell growth, survival and proliferation. “+” activation.</p>
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<p>Phosphatidylinositol 3-kinase (PI3K) protein kinase B (AKT)/mammalian target of rapamycin (mTOR) pathway, insulin resistance and hypertension. Hypercaloric diet, branched-chain amino acids (BCAAs), proinflammatory cytokines, free fatty acids (FFAs), increased salt intake, the renin–angiotensin–aldosterone system (RAAS) and salt-inducible kinase (SIK) induce mTOR hyperactivation via RTKs or insulin receptor substrates (IRS1/2). IRS phosphorylation produced by angiotensin II (Ang II) and aldosterone decreases nitric oxide (NO) synthesis. Activation of 70Ka ribosomal protein S6 kinase 1 (p70S6K1) and glycogen synthase 3 (GSK3) inhibits IRS conducing to an increased blood glucose level because GLUT will be blocked inside the cell. mTOR complex 2 (mTORC2) activates serum/glucocorticoid-regulated kinase 1 (SGK1) stimulating Na transport. mTOR over-activation is associated with synthesis of advanced end products (AGEs), reactive oxygen species (ROS), reactive nitrogen species (RNS) and lipids. Metformin has the capacity to inhibit mTOR, while rapamycin, everolimus, temsirolimus and sodium-glucose transporter protein 2 (SGLT2) block mTORC1. All these events will lead to insulin resistance (IR) and further to hypertension. “+” activation; “↓” decrease; “↑” increase.</p>
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<p>Hyperglycemia is correlated with the activation of the polyol pathway, where glucose is reduced to sorbitol by aldolase reductase (AR) and NADPH. Further, sorbitol will be oxidized to fructose by the enzyme sorbitol dehydrogenase (SDH), and NADH is generated. Fructose will be metabolized into ketone bodies, triose phosphate or carbonylic compounds such as glyoxal, methylglyoxal and 3-deoxyglucose. The last three compounds will contribute to irreversible advanced glycation end product (AGE) formation. NADPH and NADH represent sources for reactive species generation. In hyperglycemic conditions, the hexosamine biosynthesis pathway (HBP) is also activated, leading to the formation of uridine diphosphate N-acetylglucosamine (UDP-GlcNAc), which can induce protein damage. Protein kinase C (PKC) is activated by hyperglycemia, which has the capacity to activate polyol and HBP pathways. PKC activation is associated with decreased levels of nitric oxide (NO) biosynthesis and elevated levels of vascular endothelial growth factor (VEGF). All these molecular events will induce, in the end, mTOR dysregulation. “+” activation; “↑” increase; “↓” decrease.</p>
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11 pages, 278 KiB  
Article
The Prescription and Safety of Oral Antidiabetic Drugs in Outpatients with Type 2 Diabetes Mellitus: An Observational, Retrospective, Multicenter Study on the Role of Adherence in a Real-Life Primary Care Setting
by Gianmarco Marcianò, Cristina Vocca, Alessandro Casarella, Luca Gallelli, Vincenzo Rania, Caterina De Sarro, Rita Citraro, Caterina Palleria, Rosa Candida Bianco, Iolanda Fera, Antonietta Greco, Lucia Muraca, Giacinto Nanci, Carmelo Luciano Rossi, Michael Ashour, Bruno D’Agostino and Giovambattista De Sarro
Diabetology 2024, 5(3), 333-343; https://doi.org/10.3390/diabetology5030025 - 7 Aug 2024
Viewed by 448
Abstract
Introduction: Type 2 diabetes mellitus (T2DM) is a common disease burdened with significant morbidity and mortality. Despite the substantial number of new available drug treatments, adherence to therapy and adverse drug reactions (ADRs) are the major constraint in the management of this disease. [...] Read more.
Introduction: Type 2 diabetes mellitus (T2DM) is a common disease burdened with significant morbidity and mortality. Despite the substantial number of new available drug treatments, adherence to therapy and adverse drug reactions (ADRs) are the major constraint in the management of this disease. We evaluated the use, the adherence, and the safety of antidiabetic drugs in patients with T2DM. Methods: We performed an observational, retrospective, multicenter study on medical records of outpatients referred to general practitioners in Catanzaro (Calabria, Italy). Drug adherence was measured considering the packages of antidiabetic drugs prescribed at the time of admission, after three months, and 1 year later. ADRs were evaluated using the Naranjo probability scale. Collected data were analyzed using the Statistical Package for the Social Sciences. Results: During the study, we evaluated 12,170 medical records of seven general practitioners. The most prescribed drug was metformin alone (28.4%) or with other oral antidiabetics (19.6%) and then insulin (n: 354; men 190, women 164). Logistic regression showed an association between T2DM less than or equal to 5 years and low adherence (p = 0.023). During the study, we recorded 26 ADRs that were correlated with sex (women) and insulin treatment. Conclusions: this real-life study shows that patients with T2DM have a high adherence, probably related to their having a low number of ADRs. Full article
12 pages, 746 KiB  
Article
Involvement of Expression of miR33-5p and ABCA1 in Human Peripheral Blood Mononuclear Cells in Coronary Artery Disease
by Yazmín Estela Torres-Paz, Ricardo Gamboa, Giovanny Fuentevilla-Álvarez, Guillermo Cardoso-Saldaña, Rocío Martínez-Alvarado, María Elena Soto and Claudia Huesca-Gómez
Int. J. Mol. Sci. 2024, 25(16), 8605; https://doi.org/10.3390/ijms25168605 - 7 Aug 2024
Viewed by 224
Abstract
MicroRNAs (miRs) are small non-coding RNAs that regulate gene expression post-transcriptionally and are crucial in lipid metabolism. ATP-binding cassette transporter A1 (ABCA1) is essential for cholesterol efflux from cells to high-density lipoprotein (HDL). Dysregulation of miRs targeting ABCA1 can affect cholesterol homeostasis and [...] Read more.
MicroRNAs (miRs) are small non-coding RNAs that regulate gene expression post-transcriptionally and are crucial in lipid metabolism. ATP-binding cassette transporter A1 (ABCA1) is essential for cholesterol efflux from cells to high-density lipoprotein (HDL). Dysregulation of miRs targeting ABCA1 can affect cholesterol homeostasis and contribute to coronary artery disease (CAD). This study aimed to investigate the expression of miRs targeting ABCA1 in human monocytes, their role in cholesterol efflux, and their relationship with CAD. We included 50 control and 50 CAD patients. RT-qPCR examined the expression of miR-33a-5p, miR-26a-5p, and miR-144-3p in monocytes. Logistic regression analysis explored the association between these miRs and CAD. HDL’s cholesterol acceptance was analyzed using the J774A.1 cell line. Results showed that miR-26a-5p (p = 0.027) and ABCA1 (p = 0.003) expression levels were higher in CAD patients, while miR-33a-5p (p < 0.001) levels were lower. Downregulation of miR-33a-5p and upregulation of ABCA1 were linked to a lower CAD risk. Atorvastatin upregulated ABCA1 mRNA, and metformin downregulated miR-26a-5p in CAD patients. Decreased cholesterol efflux correlated with higher CAD risk and inversely with miRs in controls. Reduced miR-33a-5p expression and increased ABCA1 expression are associated with decreased CAD risk. miR deregulation in monocytes may influence atherosclerotic plaque formation by regulating cholesterol efflux. Atorvastatin and metformin could offer protective effects by modulating miR-33a-5p, miR-26a-5p, and ABCA1, suggesting potential therapeutic strategies for CAD prognosis and treatment. Full article
(This article belongs to the Special Issue MicroRNA Regulation in Human Health and Diseases)
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<p>Comparison between HC and CAD patients’ expression levels of the following in monocytes. (<b>A</b>) miR-33a-5p, (<b>B</b>) miR-144-3p, (<b>C</b>) miR-26a-5p, and (<b>D</b>) <span class="html-italic">ABCA1</span>. The data were normalized to RNU6B. The data are expressed as medians (min.–max.) (Mann–Whitney U test). * <span class="html-italic">p</span> &gt; 0.05.</p>
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<p>Cholesterol efflux from study groups; * <span class="html-italic">p</span> = 0.013. The data are expressed as means ± SE.</p>
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10 pages, 300 KiB  
Article
Metformin in Chemoprevention of Lung Cancer: A Retrospective Population-Based Cohort Study in Lithuania
by Justinas Jonusas, Ausvydas Patasius, Mingaile Drevinskaite, Adomas Ladukas, Donata Linkeviciute-Ulinskiene, Lina Zabuliene and Giedre Smailyte
Medicina 2024, 60(8), 1275; https://doi.org/10.3390/medicina60081275 - 7 Aug 2024
Viewed by 307
Abstract
Background and Objectives: This study aimed to evaluate the potential chemopreventive effect of antidiabetic medications, specifically metformin and pioglitazone, on lung cancer in patients with type 2 diabetes mellitus (T2DM). Additionally, the potential dose–response relationship for metformin use was analyzed. Methods: [...] Read more.
Background and Objectives: This study aimed to evaluate the potential chemopreventive effect of antidiabetic medications, specifically metformin and pioglitazone, on lung cancer in patients with type 2 diabetes mellitus (T2DM). Additionally, the potential dose–response relationship for metformin use was analyzed. Methods: We conducted a retrospective cohort study utilizing comprehensive national health insurance and cancer registry databases to gather a large cohort of T2DM patients. Cox proportional hazards regression models were used to assess the risk of lung cancer across different antidiabetic medication groups, adjusting for potential confounders such as age and gender. A dose–response analysis was conducted for metformin users. Results: Our results indicated that metformin users had a significantly lower lung cancer risk than the reference group (HR = 0.69, 95% CI [0.55–0.86], p = 0.001). The risk reduction increased with higher cumulative metformin doses: a metformin cumulative dose between 1,370,000 and 2,976,000 had an HR of 0.61 (95% CI [0.49–0.75], p < 0.001) vs. cumulative metformin dose >2,976,000 which had an HR of 0.35 (95% CI [0.21–0.59], p < 0.001). No significant association between pioglitazone use and the risk of lung cancer was found (HR = 1.00, 95% CI [0.25–4.02]). Conclusions: This study shows that metformin may have a dose-dependent chemopreventive effect against lung cancer in T2DM, while the impact of pioglitazone remains unclear and requires further investigation. Full article
(This article belongs to the Section Pulmonology)
13 pages, 5736 KiB  
Article
Novel Approach for Cardioprotection: In Situ Targeting of Metformin via Conductive Hydrogel System
by Ying Tan, Jierong Li, Yali Nie and Zhi Zheng
Polymers 2024, 16(15), 2226; https://doi.org/10.3390/polym16152226 - 5 Aug 2024
Viewed by 375
Abstract
Ischemia/reperfusion (I/R) injury following myocardial infarction is a major cause of cardiomyocyte death and impaired cardiac function. Although clinical data show that metformin is effective in repairing cardiac I/R injury, its efficacy is hindered by non-specific targeting during administration, a short half-life, frequent [...] Read more.
Ischemia/reperfusion (I/R) injury following myocardial infarction is a major cause of cardiomyocyte death and impaired cardiac function. Although clinical data show that metformin is effective in repairing cardiac I/R injury, its efficacy is hindered by non-specific targeting during administration, a short half-life, frequent dosing, and potential adverse effects on the liver and kidneys. In recent years, injectable hydrogels have shown substantial potential in overcoming drug delivery challenges and treating myocardial infarction. To this end, we developed a natural polymer hydrogel system comprising methacryloylated chitosan and methacryloylated gelatin modified with polyaniline conductive derivatives. In vitro studies demonstrated that the optimized hydrogel exhibited excellent injectability, biocompatibility, biodegradability, suitable mechanical properties, and electrical conductivity. Incorporating metformin into this hydrogel significantly extended the administration cycle, mitigated mitochondrial damage, decreased abnormal ROS production, and enhanced cardiomyocyte function. Animal experiments indicated that the metformin/hydrogel system reduced arrhythmia incidence, infarct size, and improved cardiac mitochondrial and overall cardiac function, promoting myocardial repair in I/R injury. Overall, the metformin-loaded conductive hydrogel system effectively mitigates mitochondrial oxidative damage and improves cardiomyocyte function, thereby offering a theoretical foundation for the potential application of metformin in cardioprotection. Full article
(This article belongs to the Special Issue Advances in Biomimetic Smart Hydrogels)
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<p>Preparation of CSMA/Pam-GelMA hydrogels. (<b>A</b>) Preparation process of CSMA/Pam-GelMA hydrogels. (<b>B</b>) <sup>1</sup>H NMR spectra of CSMA and Pam-GelMA. (<b>C</b>) FT-IR spectra of CS, CSMA, gelatin, and Pam-GelMA. (<b>D</b>) Photographs of different formulations forming hydrogels. (<b>E</b>) Photographs of different formulated hydrogels subjected to equal pressure.</p>
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<p>Characterization of CSMA/Pam-GelMA hydrogels. (<b>A</b>) SEM images of CSMA/Pam-GelMA hydrogels with different formulations. (<b>B</b>) Rheological time-scanning plots of CSMA/Pam-GelMA hydrogels. (<b>C</b>) Rheological frequency-scanning plots of CSMA/Pam-GelMA hydrogels. (<b>D</b>) CV curve of CSMA/Pam-GelMA hydrogels. (<b>E</b>) Photograph of injectability of CSMA/Pam-GelMA hydrogel. (<b>F</b>) Metf release cycle at pH 6.0 and pH 7.4.</p>
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<p>Effect of metf/hydrogel on CM activity. (<b>A</b>) MTT assay to detect effect of different components on CM cytocompatibility. (<b>B</b>) Live/dead cell assay to assess effect of hydrogel on CM activity in culture for one week. (<b>C</b>) DHE staining kit to detect CM oxidative damage. (<b>D</b>) Representative TEM images of cardiac muscle mitochondria from each experimental group were examined. (<b>E</b>) Fluorescence images of JC-1 were taken to evaluate membrane potential of mitochondria in CM in all groups. (<b>F</b>) Quantitative fluorescence analyses are from JC-1. (n = 3, *** <span class="html-italic">p</span> &lt; 0.001).</p>
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<p>Effect of metf/hydrogel on cellular activity in infarcted region. (<b>A</b>) DHE staining of infarcted areas in all groups. (<b>B</b>) ROS staining of infarcted region in all groups. (<b>C</b>) Fluorescence quantification of DHE staining in all groups. (<b>D</b>) Bioelectron microscopy of myocardial tissue in infarcted regions of all groups (scale bar: 2 μm). (n = 3, *** <span class="html-italic">p</span> &lt; 0.001).</p>
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<p>Effects of metf/hydrogel treatment on heart in rats with MI after 28 days of treatment. (<b>A</b>) H&amp;E staining of MI in all groups. (<b>B</b>) Masson staining of infarcted area in all groups. (<b>C</b>,<b>D</b>) Quantitative analysis of myocardial wall thickness and infarct area in all groups. (<b>E</b>) Representative ECGs of all groups after 4 weeks of treatment (n = 3, *** <span class="html-italic">p</span> &lt; 0.001).</p>
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<p>Effect of metf/hydrogel on cardiac function in MI rats. (<b>A</b>) ECHO was performed on SD rats from different treatment groups after 4 weeks of treatment. (<b>B</b>–<b>E</b>) LVEF, LVFS, LVIDd, and LVIDs obtained from ECHO. (n = 3, *** <span class="html-italic">p</span> &lt; 0.001).</p>
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11 pages, 4743 KiB  
Article
Extraction, Characterization, and Nutraceutical Potential of Prosthechea karwinskii Orchid for Insulin Resistance and Oxidative Stress in Wistar Rats
by Gabriela Soledad Barragán-Zarate, Luicita Lagunez-Rivera, Alfonso Alexander-Aguilera, Rodolfo Solano and Gerard Vilarem
Foods 2024, 13(15), 2432; https://doi.org/10.3390/foods13152432 - 1 Aug 2024
Viewed by 396
Abstract
Prosthechea karwinskii is an endemic orchid of Mexico with cultural significance for its ornamental, food, religious, and medicinal uses. In traditional medicine, diabetic patients use the leaves of this plant to lower glucose levels. The present study evaluated the effect of P. karwinskii [...] Read more.
Prosthechea karwinskii is an endemic orchid of Mexico with cultural significance for its ornamental, food, religious, and medicinal uses. In traditional medicine, diabetic patients use the leaves of this plant to lower glucose levels. The present study evaluated the effect of P. karwinskii leaves extract on the antioxidant enzymes superoxide dismutase (SOD) and catalase (CAT) in a model of obese rats with insulin resistance for its nutraceutical potential to reduce insulin resistance and oxidative stress. Obesity and insulin resistance were induced with 40% sucrose in water for 20 weeks. Four groups (control rats, obese rats, obese rats administered the extract, and obese rats administered metformin) were evaluated. Extract compounds were identified by UHPLC-ESI-qTOF-MS/MS. Glucose, insulin, triglyceride, and insulin resistance indices (HOMA-IR and TyG), as well as the activity of the antioxidant enzymes, increased in rats in the obese group. Administration of P. karwinskii extract and metformin reduced glucose, insulin, triglyceride, and insulin resistance indices and antioxidant enzyme activity to values similar to those of the control group. Therefore, this study shows the nutraceutical potential of P. karwinskii extract as an ingredient in the formulation of dietary supplements or functional foods to help treat diseases whose pathophysiology is related to oxidative stress and insulin resistance. Full article
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<p>Glucose (<b>a</b>), insulin (<b>b</b>), and (<b>c</b>) triglyceride levels and HOMA-IR (<b>d</b>) and TyG (<b>e</b>) insulin resistance indices. Values expressed as means ± SDs. * Indicates a significant difference (<span class="html-italic">p</span> ˂ 0.05) with respect to CG; ** indicates a significant difference (<span class="html-italic">p</span> ˂ 0.05) with respect to OG. CG: control group, OG: obese rats, PK: obese rats that received extract, and MET: obese rats that received metformin.</p>
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<p>Superoxide dismutase enzyme activity (SOD) (<b>a</b>) and catalase enzyme activity (CAT) (<b>b</b>). Values expressed as means ± SDs. * Indicates a significant difference (<span class="html-italic">p</span> ˂ 0.05) with respect to GC; ** indicates a significant difference (<span class="html-italic">p</span> ˂ 0.05) with respect to OG. CG: control group, OG: obese rats, PK: obese rats that received extract, and MET: obese rats that received metformin.</p>
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21 pages, 1497 KiB  
Review
Unlocking the Potential: Caloric Restriction, Caloric Restriction Mimetics, and Their Impact on Cancer Prevention and Treatment
by Ulises Edgardo De-Leon-Covarrubias, Jose Juan Perez-Trujillo, Sheila Adela Villa-Cedillo, Alejandra Guadalupe Martinez-Perez, Carlos Roberto Montes-de-Oca-Saucedo, Maria de Jesus Loera-Arias, Aracely Garcia-Garcia, Odila Saucedo-Cardenas and Roberto Montes-de-Oca-Luna
Metabolites 2024, 14(8), 418; https://doi.org/10.3390/metabo14080418 - 30 Jul 2024
Viewed by 335
Abstract
Caloric restriction (CR) and its related alternatives have been shown to be the only interventions capable of extending lifespan and decreasing the risk of cancer, along with a reduction in burden in pre-clinical trials. Nevertheless, the results from clinical trials have not been [...] Read more.
Caloric restriction (CR) and its related alternatives have been shown to be the only interventions capable of extending lifespan and decreasing the risk of cancer, along with a reduction in burden in pre-clinical trials. Nevertheless, the results from clinical trials have not been as conclusive as the pre-clinical results. Recognizing the challenges associated with long-term fasting, the application of caloric restriction mimetics (CRMs), pharmacological agents that mimic the molecular effects of CR, to harness the potential benefits while overcoming the practical limitations of fasting has resulted in an interesting alternative. This review synthesizes the findings of diverse clinical trials evaluating the safety and efficacy of CR and CRMs. In dietary interventions, a fast-mimicking diet was the most tolerated to reduce tumoral growth markers and chemotherapy side effects. CRMs were well tolerated, and metformin and aspirin showed the most promising effect in reducing cancer risk in a selected group of patients. The application of CR and/or CRMs shows promising effects in anti-cancer therapy; however, there is a need for more evidence to safely include these interventions in standard-of-care therapies. Full article
(This article belongs to the Topic Cancer Cell Metabolism (2nd Edition))
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<p>Tumor-altered pathways and CR molecular targets. (<b>A</b>) One of the commonly altered pathways in tumor cells is the PI3K/AKT/mTOR pathway, which leads to increased protein synthesis through S6K1 activation and the upregulation of HIF1α. HIF1α further promotes glycolytic intermediaries such as hexokinase (HK), pyruvate dehydrogenase kinase (PDK), and lactate dehydrogenase (LDH). Additionally, it induces the secretion of growth factors like insulin-like growth factor (IGF-1), transforming growth factor beta (TGF-β), and vascular endothelial growth factor (VEGF). These changes collectively enhance cell growth, proliferation, and chemoresistance. (<b>B</b>) When a caloric-restriction intervention is applied, such as glucose starvation, the increased AMP levels activate AMPK. This activation results in the inhibition of AKT and mTOR pathways and triggers a response mediated by p53 and p21, leading to interrupted protein synthesis and cell cycle arrest or apoptosis. The energy deficit also activates the SIRT pathways, which downregulates HIF1α, and the Nrf2 pathway, which enhances antioxidant defenses (e.g., superoxide dismutase SOD1 and SOD2) and reduces reactive oxygen species (ROS). Sky blue background shows tumor-altered pathways in non-caloric restriction (normal) diet, meanwhile red background shows the pathways during caloric restriction diet. Figure created with <a href="http://BioRender.com" target="_blank">BioRender.com</a>. Note: Arrows indicate activation, while dashed bar lines indicate inactivation.</p>
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<p>Caloric restriction mimetics and their targets. Metformin, aspirin, resveratrol, and rapamycin are the most common CRMs used in preclinical and clinical research. Their principal target is the direct or indirect activation of the master regulators AMPK and SIRT. Activation of these master regulators can lead to the inactivation of key growth and division pathways such as PI3K/AKT/mTOR and HIF1α. Figure created with <a href="http://BioRender.com" target="_blank">BioRender.com</a>. Note: arrows indicate activation, while dashed bar lines indicate inactivation.</p>
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9 pages, 1383 KiB  
Brief Report
Changes in the Sensitivity of MCF-7 and MCF-7/DX Breast Cancer Cells to Cytostatic in the Presence of Metformin
by Justyna Płonka-Czerw, Luiza Żyrek and Małgorzata Latocha
Molecules 2024, 29(15), 3531; https://doi.org/10.3390/molecules29153531 - 27 Jul 2024
Viewed by 521
Abstract
Multidrug resistance is a serious problem in modern medicine and the reason for the failure of various therapies. A particularly important problem is the occurrence of multidrug resistance in cancer therapies which affects many cancer patients. Observations on the effect of metformin—a well-known [...] Read more.
Multidrug resistance is a serious problem in modern medicine and the reason for the failure of various therapies. A particularly important problem is the occurrence of multidrug resistance in cancer therapies which affects many cancer patients. Observations on the effect of metformin—a well-known hypoglycemic drug used in the treatment of type 2 diabetes—on cancer cells indicate the possibility of an interaction of this substance with drugs already used and, as a result, an increase in the sensitivity of cancer cells to cytostatics. The aim of this study was to evaluate the effect of metformin on the occurrence of multidrug resistance of breast cancer cells. The MCF-7-sensitive cell line and the MCF-7/DX cytostatic-resistant cell line were used for this study. WST-1 and LDH assays were used to evaluate the effects of metformin and doxorubicin on cell proliferation and viability. The effect of metformin on increasing the sensitivity of MCF-7 and MCF-7/DX cells to doxorubicin was evaluated in an MDR test. The participation of metformin in increasing the sensitivity of resistant cells to the effect of the cytostatic (doxorubicin) has been demonstrated. Full article
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<p>(<b>a</b>) The effect of different doses of metformin (1.56–100 mM), doxorubicin (1.56–100 µM) and mixture of doxorubicin (1.56–100 µM) with metformin (12.5 mM and 50 mM) on the metabolic activity of MCF-7 and MCF-7/DX cells (WST-1 assay). (<b>b</b>) The cytotoxicity effect of different doses of metformin (1.56–100 mM), doxorubicin (1.56–100 µM) and mixture of doxorubicin (1.56–100 µM) with metformin (12.5 mM and 50 mM) in the MCF-7 and MCF-7/DX in vitro cultures (LDH assay). (<b>c</b>) The effectiveness of different doses of metformin (1.56–100 mM) in overcoming the resistance of the MCF-7 and MCF-7/DX cells to doxorubicin (MDR assay). Statistical significance is set to <span class="html-italic">p</span> ≤ 0.05 (*).</p>
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<p>(<b>a</b>) The effect of different doses of metformin (1.56–100 mM), doxorubicin (1.56–100 µM) and mixture of doxorubicin (1.56–100 µM) with metformin (12.5 mM and 50 mM) on the metabolic activity of MCF-7 and MCF-7/DX cells (WST-1 assay). (<b>b</b>) The cytotoxicity effect of different doses of metformin (1.56–100 mM), doxorubicin (1.56–100 µM) and mixture of doxorubicin (1.56–100 µM) with metformin (12.5 mM and 50 mM) in the MCF-7 and MCF-7/DX in vitro cultures (LDH assay). (<b>c</b>) The effectiveness of different doses of metformin (1.56–100 mM) in overcoming the resistance of the MCF-7 and MCF-7/DX cells to doxorubicin (MDR assay). Statistical significance is set to <span class="html-italic">p</span> ≤ 0.05 (*).</p>
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<p>Diagram showing molecular targets for metformin determined from drug structure using the SwissTargetPrediction program.</p>
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20 pages, 2880 KiB  
Article
Overexpression of miR-199b-5p in Colony Forming Unit-Hill’s Colonies Positively Mediates the Inflammatory Response in Subclinical Cardiovascular Disease Model: Metformin Therapy Attenuates Its Expression
by Sherin Bakhashab, Rosie Barber, Josie O’Neill, Catherine Arden and Jolanta U. Weaver
Int. J. Mol. Sci. 2024, 25(15), 8087; https://doi.org/10.3390/ijms25158087 - 25 Jul 2024
Viewed by 372
Abstract
Well-controlled type 1 diabetes (T1DM) is characterized by inflammation and endothelial dysfunction, thus constituting a suitable model of subclinical cardiovascular disease (CVD). miR-199b-5p overexpression in murine CVD has shown proatherosclerotic effects. We hypothesized that miR-199b-5p would be overexpressed in subclinical CVD yet downregulated [...] Read more.
Well-controlled type 1 diabetes (T1DM) is characterized by inflammation and endothelial dysfunction, thus constituting a suitable model of subclinical cardiovascular disease (CVD). miR-199b-5p overexpression in murine CVD has shown proatherosclerotic effects. We hypothesized that miR-199b-5p would be overexpressed in subclinical CVD yet downregulated following metformin therapy. Inflammatory and vascular markers were measured in 29 individuals with T1DM and 20 matched healthy controls (HCs). miR-199b-5p expression in CFU-Hill’s colonies was analyzed from each study group, and correlations with inflammatory/vascular health indices were evaluated. Significant upregulation of miR-199b-5p was observed in T1DM, which was significantly downregulated by metformin. miR-199b-5p correlated positively with vascular endothelial growth factor-D and c-reactive protein (CRP: nonsignificant). ROC analysis determined miR-199b-5p to define subclinical CVD by discriminating between HCs and T1DM individuals. ROC analyses of HbA1c and CRP showed that the upregulation of miR-199b-5p in T1DM individuals defined subclinical CVD at HbA1c > 44.25 mmol and CRP > 4.35 × 106 pg/mL. Ingenuity pathway analysis predicted miR-199b-5p to inhibit the target genes SIRT1, ETS1, and JAG1. Metformin was predicted to downregulate miR-199b-5p via NFATC2 and STAT3 and reverse its downstream effects. This study validated the antiangiogenic properties of miR-199b-5p and substantiated miR-199b-5p overexpression as a biomarker of subclinical CVD. The downregulation of miR-199b-5p by metformin confirmed its cardio-protective effect. Full article
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<p>The comparison of miR-199b-5p expression in CFU-Hill’s colonies between healthy controls and T1DM individuals before (T1DM) and after (T1DM + M) metformin treatment. Fold change between miR-199b-5p mean 2<sup>(ΔΔCq)</sup> values used as a measure of expression. Data were analyzed by one-way ANOVA followed by Tukey test and presented as means ± SD: * <span class="html-italic">p</span> &lt; 0.05, *** <span class="html-italic">p</span> &lt; 0.001.</p>
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<p>Receiver operating characteristic (ROC) curve analysis of (<b>A</b>) miR-199b-5p in discriminating between healthy controls and T1DM individuals (AUC = 0.750; <span class="html-italic">p</span> = 0.0404), (<b>B</b>) HbA1c (AUC= 1.000; <span class="html-italic">p</span> &lt; 0.0001), and (<b>C</b>) CRP (AUC = 0.900; <span class="html-italic">p</span> = 0.0010). ROC curve analysis was performed to determine optimal cutoff values. HbA1c: glycated hemoglobin; CRP: c-reactive protein.</p>
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<p>The relationship between miR-199b-5p expression in CFU-Hill’s colonies and plasma levels of VEGF-D. (<b>A</b>) Receiver operating characteristic (ROC) curve analysis of VEGF-D. (<b>B</b>) Correlation between miR-199b-5p expression in CFU-Hill’s colonies and plasma levels of VEGF-D. ROC curve analysis was performed to determine optimal cutoff values, while correlations were assessed using linear regression analysis. VEGF: vascular endothelial growth factor.</p>
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<p>Ingenuity Pathway Analysis (IPA) prediction network of miR-199b-5p using this study’s data and its mRNA targets supporting its association with cardiovascular disease. Four pathways were considered relevant in this study: inflammatory response, vasculogenesis, angiogenesis, and atherosclerosis. Red signifies upregulation of miR-199b-5p, orange signifies predicted activation, and blue signifies predicted inhibition. Solid lines represent a direct interaction, and dashed lines represent an indirect interaction. All interactions have a value of <span class="html-italic">p</span> &lt; 0.05. CDH5: cadherin 5; CRP: c-reactive protein; ETS1: ETS proto-oncogene 1, transcription factor; HBA1/HBA2: glycated hemoglobin subunit α1/2; HGF: hepatocyte growth factor; IGF1: insulin-like growth factor 1; ITGβ1: integrin subunit β1; JAG1: jagged canonical notch ligand 1; KLF2: Krüppel-like factor 2; MMP1: matrix metallopeptidase 1; SFTPA1: surfactant protein A1; SHC1: SHC-transforming protein 1; SIRT1: sirtuin 1; VEGFD: vascular endothelial growth factor D.</p>
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<p>Ingenuity Pathway Analysis (IPA) prediction network of miR-199b-5p molecular targets and functional pathways following metformin intervention. Red signifies upregulation of metformin, orange signifies predicted activation, and blue signifies predicted inhibition. Solid lines represent a direct interaction, and dashed lines represent an indirect interaction. All interactions have a value of <span class="html-italic">p</span> &lt; 0.05. CDH5: cadherin 5; CRP: c-reactive protein; ETS1: ETS proto-oncogene 1, transcription factor; HBA1/HBA2: glycated hemoglobin subunit α1/2; HGF: hepatocyte growth factor; IGF1: insulin-like growth factor 1; ITGβ1: integrin subunit β1; JAG1: jagged canonical notch ligand 1; KLF2: Krüppel-like factor 2; MAPK8: mitogen-activated protein kinase 8; mir-199: micro-RNA-199; MMP1: matrix metallopeptidase-1; NFATC2: nuclear factor of activated T cells 2; RELA: RELA proto-oncogene, NF-κB subunit; SFTPA1: surfactant protein A1; SHC1: SHC-transforming protein 1; SIRT1: sirtuin 1; STAT3: signal transducer and activator of transcription 3; VEGFD: vascular endothelial growth factor D.</p>
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<p>Schematic summary of the findings of this research following the study in T1DM individuals with subclinical CVD. Upregulated miR-199b-5p, CRP, TNF-α, and thrombomodulin demonstrated proatherogenic effects and contributed to increased CVD risk in T1DM individuals. Downregulation of antiatherogenic CFU-Hill’s colonies, CD34<sup>+</sup> stem cells, and CD34<sup>+</sup>CD133<sup>+</sup> stem cells further contributed to elevated T1DM-related CVD risk. Upregulation of VEGF-D proposed a pro-atherosclerotic role in T1DM. Created using BioRender.com. T1DM: type 1 diabetes mellitus; CVD: cardiovascular disease; miR: micro-RNA; CRP: c-reactive protein; TNF: tumor necrosis factor; CD: cluster of differentiation; VEGF: vascular endothelial growth factor. The red color denoted increased and blue color decreased.</p>
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<p>Schematic summary of the findings of this research following metformin intervention. Metformin inhibited miR-199b-5p and subsequently downregulated CRP and TNF-α, thus contributing to reduced CVD risk in T1DM individuals. Upregulation of antiatherogenic CFU-Hill’s colonies, CD34<sup>+</sup> stem cells, and CD34<sup>+</sup>CD133<sup>+</sup> stem cells further contributed to reduced T1DM-related CVD risk. Downregulated thrombomodulin reflected the reduced level of inflammation. Downregulation of VEGF-D reduced its proatherosclerotic role in T1DM. Created using BioRender.com. T1DM: type 1 diabetes mellitus; CVD: cardiovascular disease; miR: micro-RNA; CRP: c-reactive protein; TNF: tumor necrosis factor; CD: cluster of differentiation; VEGF: vascular endothelial growth factor. The red color denoted increased and blue color decreased.</p>
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16 pages, 2197 KiB  
Article
The Association of Metformin, Other Antidiabetic Medications, and Statins with the Prognosis of Hepatocellular Carcinoma in Patients with Type 2 Diabetes: A Retrospective Cohort Study
by Iida Tuunanen, Ari Hautakoski, Heikki Huhtamäki, Martti Arffman, Reijo Sund, Ulla Puistola, Peeter Karihtala, Arja Jukkola and Elina Urpilainen
Biomedicines 2024, 12(8), 1654; https://doi.org/10.3390/biomedicines12081654 - 24 Jul 2024
Viewed by 435
Abstract
This study aimed to explore whether the prediagnostic use of metformin and statins is associated with the prognosis of patients with hepatocellular carcinoma (HCC) and type 2 diabetes. We identified 1383 eligible individuals who had both type 2 diabetes and HCC diagnosed between [...] Read more.
This study aimed to explore whether the prediagnostic use of metformin and statins is associated with the prognosis of patients with hepatocellular carcinoma (HCC) and type 2 diabetes. We identified 1383 eligible individuals who had both type 2 diabetes and HCC diagnosed between 1998 and 2017 from several Finnish registers. Cox models were fitted for cause-specific and all-cause mortality in relation to the use of antidiabetic medications and statins prior to the HCC diagnosis. Prediagnostic metformin use was associated with decreased overall mortality (hazard ratio 0.84, 95% confidence interval 0.74–0.94) compared with nonuse in patients with type 2 diabetes. Similarly, slightly decreased HCC mortality and other-cause mortality were observed among metformin users. The results were inconclusive regarding metformin use and both overall and HCC mortality among patients with localized HCC. No discernible contrast between statin users and nonusers was found in overall mortality nor HCC mortality in either the whole cohort or patients with localized cancer. Full article
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<p>Flowchart of the cohort selection process.</p>
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<p>Cumulative overall, hepatocellular carcinoma (HCC) and other-cause mortality curves for the whole cohort according to metformin (<b>A</b>–<b>C</b>) and statin (<b>D</b>–<b>F</b>) use. Curves (<b>A</b>,<b>D</b>) represent overall mortality, curves (<b>B</b>) and E HCC mortality, and curves (<b>C</b>,<b>F</b>) other-cause mortality.</p>
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<p>Cumulative overall, HCC, and other-cause mortality curves for the subgroup of patients with local HCC according to metformin (<b>A</b>–<b>C</b>) and statin (<b>D</b>–<b>F</b>) use. Curves (<b>A</b>,<b>D</b>) represent overall mortality, curves (<b>B</b>) and E HCC mortality, and curves (<b>C</b>,<b>F</b>) other-cause mortality.</p>
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<p>Metformin has both direct and indirect effects on cancer cells. It activates AMP-activated protein kinase (AMPK), leading to the inhibition of the mammalian target of rapamycin (mTOR). It also sensitizes tissues to insulin, reduces hepatic gluconeogenesis, and decreases circulating insulin levels. This leads indirectly to reduced phosphatidylinositol-3-kinase (PI3K) signaling. IGF-1 = insulin-like growth factor 1, ACC = acetyl-CoA carboxylase, HMG-CoA = 3-hydroxy-3-methyl-glutarylcoenzyme A, p53 = tumor protein p53, AKT = serine/threonine-specific protein kinase, and STAT3 = signal transducer and activator of transcription 3, ↓ decreasing effect, ⊥ inhibitory effect [<a href="#B25-biomedicines-12-01654" class="html-bibr">25</a>,<a href="#B26-biomedicines-12-01654" class="html-bibr">26</a>].</p>
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<p>Statins may have multiple antitumoral mechanisms in hepatocellular carcinoma. Statins seems to increase tumor cell apoptosis as well as decrease both tumor cell invasion and proliferation. Additionally, statins decrease angiogenesis, inflammation, liver fibrosis, and hepatitis C virus pathogenesis. ↓ decreasing effect, ↑ increasing effect [<a href="#B32-biomedicines-12-01654" class="html-bibr">32</a>].</p>
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14 pages, 647 KiB  
Article
Autoimmune Thyroiditis Mitigates the Effect of Metformin on Plasma Prolactin Concentration in Men with Drug-Induced Hyperprolactinemia
by Robert Krysiak, Marcin Basiak, Witold Szkróbka and Bogusław Okopień
Pharmaceuticals 2024, 17(8), 976; https://doi.org/10.3390/ph17080976 - 23 Jul 2024
Viewed by 351
Abstract
Metformin inhibits the secretory function of overactive anterior pituitary cells, including lactotropes. In women of childbearing age, this effect was absent if they had coexisting autoimmune (Hashimoto) thyroiditis. The current study was aimed at investigating whether autoimmune thyroiditis modulates the impact of metformin [...] Read more.
Metformin inhibits the secretory function of overactive anterior pituitary cells, including lactotropes. In women of childbearing age, this effect was absent if they had coexisting autoimmune (Hashimoto) thyroiditis. The current study was aimed at investigating whether autoimmune thyroiditis modulates the impact of metformin on the plasma prolactin concentration in men. This prospective cohort study included two groups of middle-aged or elderly men with drug-induced hyperprolactinemia, namely subjects with concomitant Hashimoto thyroiditis (group A) and subjects with normal thyroid function (group B), who were matched for baseline prolactin concentration and insulin sensitivity. Titers of thyroid peroxidase and thyroglobulin antibodies, levels of C-reactive protein, markers of glucose homeostasis, concentrations of pituitary hormones (prolactin, thyrotropin, gonadotropins, and adrenocorticotropic hormone), free thyroxine, free triiodothyronine, testosterone, and insulin growth factor-1 were measured before and six months after treatment with metformin. Both study groups differed in titers of both antibodies and concentrations of C-reactive protein. The drug reduced the total and monomeric prolactin concentration only in group B, and the impact on prolactin correlated with the improvement in insulin sensitivity and systemic inflammation. There were no differences between the follow-up and baseline levels of the remaining hormones. The results allow us to conclude that autoimmune thyroiditis mitigates the impact of metformin on prolactin secretion in men. Full article
(This article belongs to the Special Issue Advancements in Cardiovascular and Antidiabetic Drug Therapy)
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<p>Flow the patients through the study.</p>
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23 pages, 1551 KiB  
Review
Diabetes and Osteoarthritis: Exploring the Interactions and Therapeutic Implications of Insulin, Metformin, and GLP-1-Based Interventions
by Iryna Halabitska, Liliia Babinets, Valentyn Oksenych and Oleksandr Kamyshnyi
Biomedicines 2024, 12(8), 1630; https://doi.org/10.3390/biomedicines12081630 - 23 Jul 2024
Viewed by 618
Abstract
Diabetes mellitus (DM) and osteoarthritis (OA) are prevalent chronic conditions with shared pathophysiological links, including inflammation and metabolic dysregulation. This study investigates the potential impact of insulin, metformin, and GLP-1-based therapies on OA progression. Methods involved a literature review of clinical trials and [...] Read more.
Diabetes mellitus (DM) and osteoarthritis (OA) are prevalent chronic conditions with shared pathophysiological links, including inflammation and metabolic dysregulation. This study investigates the potential impact of insulin, metformin, and GLP-1-based therapies on OA progression. Methods involved a literature review of clinical trials and mechanistic studies exploring the effects of these medications on OA outcomes. Results indicate that insulin, beyond its role in glycemic control, may modulate inflammatory pathways relevant to OA, potentially influencing joint health. Metformin, recognized for its anti-inflammatory properties via AMPK activation, shows promise in mitigating OA progression by preserving cartilage integrity and reducing inflammatory markers. GLP-1-based therapies, known for enhancing insulin secretion and improving metabolic profiles in DM, also exhibit anti-inflammatory effects that may benefit OA by suppressing cytokine-mediated joint inflammation and supporting cartilage repair mechanisms. Conclusions suggest that these medications, while primarily indicated for diabetes management, hold therapeutic potential in OA by targeting common underlying mechanisms. Further clinical trials are warranted to validate these findings and explore optimal therapeutic strategies for managing both DM and OA comorbidities effectively. Full article
(This article belongs to the Special Issue New Advances in Insulin—100 Years since Its Discovery)
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<p>Illustration depicting the multifaceted effects of insulin on immune cells (T cells and macrophages), chondrocytes, and osteoclasts, emphasizing its regulatory role in immune response modulation, cartilage maintenance, and bone metabolism. Th17—T helper 17 cells, Glut1—Glucose transporter 1, mTOR—mammalian target of rapamycin, MMP-13—Matrix metalloproteinase-13, IL-1β—Interleukin-1 beta, IL-8—Interleukin-8, PGE2—Prostaglandin E2, M1—M1 macrophages (classically activated macrophages), M2—M2 macrophages (alternatively activated macrophages), RANK—Receptor activator of nuclear factor kappa-B, RANKL—RANK ligand. <a href="#biomedicines-12-01630-f001" class="html-fig">Figure 1</a> has been created in <a href="http://BioRender.com" target="_blank">BioRender.com</a> (accessed on 2 July 2024).</p>
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<p>Metformin’s activation of AMP-activated protein kinase (AMPK) leads to the inhibition of mTOR (mammalian target of rapamycin), a pivotal regulator of lymphocyte immunometabolism and the equilibrium between pro-inflammatory and anti-inflammatory cell populations within joint tissues. This inhibition results in decreased production of pro-inflammatory Th1 and Th17 cells, along with M1 macrophages, thereby promoting a predominance of anti-inflammatory Treg cells and M2 macrophages. ATP—Adenosine triphosphate, AMP—Adenosine monophosphate, AMPK—AMP-activated protein kinase, mTORC1—Mechanistic target of rapamycin complex 1, mTORC2—Mechanistic target of rapamycin complex 2, MLST8 (MLST8 protein)—mammalian lethal with SEC13 protein 8, PRAS40—Proline-rich AKT substrate 40 kDa, Ras—Rat sarcoma protein, Raf—Rapidly accelerated fibrosarcoma protein, MEK—mitogen-activated protein kinase kinase, ERK—extracellular signal-regulated kinase, RSK—Ribosomal S6 kinase, PI3K—phosphoinositide 3-kinase, Akt—protein kinase B (Akt), TSC1/2—tuberous sclerosis complex 1/2, Rheb—Ras homolog enriched in brain, GDP—Guanosine diphosphate, MSIN1—MAPK (mitogen-activated protein kinase)-interacting protein 1, MLSTS (MLSTS protein)—mammalian lethal with SEC13 protein, Reg A/B (regulatory proteins A/B), GTP—Guanosine triphosphate, Reg C/D (regulatory proteins C/D), Treg—regulatory T cells, M1—M1 macrophages (classically activated macrophages), M2—M2 macrophages (alternatively activated macrophages), Th1—T helper 1 cells, Th17—T helper 17 cells. <a href="#biomedicines-12-01630-f002" class="html-fig">Figure 2</a> has been created in <a href="http://BioRender.com" target="_blank">BioRender.com</a> (accessed on 2 July 2024).</p>
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13 pages, 2544 KiB  
Article
Astragalus Polysaccharides and Metformin May Have Synergistic Effects on the Apoptosis and Ferroptosis of Lung Adenocarcinoma A549 Cells
by I-Yun Lee, Ting-Chung Wang, Yu-Jen Kuo, Wei-Tai Shih, Pei-Rung Yang, Cheng-Ming Hsu, Yu-Shih Lin, Ren-Shyang Kuo and Ching-Yuan Wu
Curr. Issues Mol. Biol. 2024, 46(8), 7782-7794; https://doi.org/10.3390/cimb46080461 - 23 Jul 2024
Viewed by 302
Abstract
Astragalus polysaccharides (APSs), the compounds extracted from the common herb Astragalus membranaceus, have been extensively studied for their antitumor properties. In this study, we investigated the effect of APS on lung adenocarcinoma A549 cells. The effects of APS and the anti-diabetic drug metformin [...] Read more.
Astragalus polysaccharides (APSs), the compounds extracted from the common herb Astragalus membranaceus, have been extensively studied for their antitumor properties. In this study, we investigated the effect of APS on lung adenocarcinoma A549 cells. The effects of APS and the anti-diabetic drug metformin on apoptosis and ferroptosis were compared. Furthermore, the combination treatment of APS and metformin was also investigated. We found that APS not only reduced the growth of lung cancer cells but also had a synergistic effect with metformin on A549 cells. The study results showed that it may be promising to use APS and metformin as a combination therapy for the treatment of lung adenocarcinoma. Full article
(This article belongs to the Section Molecular Plant Sciences)
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<p>Synergistic effect of APS and metformin on A549 cell viability. A549 cell viability under the treatment of (<b>a</b>,<b>b</b>) APS/metformin alone for (<b>a</b>) 24 h and (<b>b</b>) for 48 h. (<b>c</b>,<b>d</b>) APS in combination with different concentrations of metformin after treatment of (<b>c</b>) 24 h and (<b>d</b>) 48 h. The combination group significantly decreased compared to using either APS or metformin alone. All the results are representative of at least three independent experiments. (Error bars = mean ± S.E.M. Asterisks mark samples significantly different from control group with (*) <span class="html-italic">p</span> &lt; 0.05; (**) with <span class="html-italic">p</span> &lt; 0.01; (***) with <span class="html-italic">p</span> &lt; 0.001).</p>
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<p>The apoptotic effect on A549 cells of APS, metformin detected by flow cytometry with annexin V-FITC/PI dual staining: (<b>a</b>,<b>c</b>) A549 cells treated for 24 h and (<b>b</b>,<b>d</b>) for 48 h. (Error bars = mean ± S.E.M. Asterisks mark samples significantly different from control group with (**) with <span class="html-italic">p</span> &lt; 0.01; (***) with <span class="html-italic">p</span> &lt; 0.001).</p>
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<p>The mitochondrial depolarization stained with Mitoscreen JC-1 assay detected by flow cytometry. Dot plots showing depolarisation of mitochondria in treated A549 cells. The percentage of events in the upper gate (P2) and the percentage of events in the (P3) represent the population of treated A549 cells with normal and depolarised mitochondria, respectively. (<b>a</b>,<b>c</b>) A549 cells treated for 24 h and (<b>b</b>,<b>d</b>) for 48 h. (Error bars = mean ± S.E.M. Asterisks mark samples significantly different from control group with (*) <span class="html-italic">p</span> &lt; 0.05; (**) with <span class="html-italic">p</span> &lt; 0.01; (***) with <span class="html-italic">p</span> &lt; 0.001).</p>
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<p>A549 were treated with indicated treatments for (<b>a</b>) 24 h and (<b>b</b>) 48 h and then harvested. The prepared cell protein was immunoblotted with polyclonal antibodies specific for PARP and cleaved PARP. Vinculin was used as an internal loading control. (Error bars = mean ± S.E.M. Asterisks mark samples significantly different from control group with (*) <span class="html-italic">p</span> &lt; 0.05; (**) with <span class="html-italic">p</span> &lt; 0.01).</p>
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<p>Effect of APS, metformin, and their combination on ferroptosis of A549 cells in vitro. The A549 cells were treated with either APS, metformin, or their combination under different concentrations for 24 h and then collected for the following test: (<b>a</b>) ROS assay; (<b>b</b>) MAD assay; (<b>c</b>) GSH levels; (<b>d</b>) Western blot for GPx4 protein. B-actin was used as the internal control. (Error bars = mean ± S.E.M. Asterisks mark samples significantly different from control group with (*) <span class="html-italic">p</span> &lt; 0.05; (**) with <span class="html-italic">p</span> &lt; 0.01; (***) with <span class="html-italic">p</span> &lt; 0.001).</p>
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17 pages, 4354 KiB  
Review
Impact of Different Anti-Hyperglycaemic Treatments on Bone Turnover Markers and Bone Mineral Density in Type 2 Diabetes Mellitus Patients: A Systematic Review and Meta-Analysis
by Md Sadman Sakib Saadi, Rajib Das, Adhithya Mullath Ullas, Diane E. Powell, Emma Wilson, Ioanna Myrtziou, Chadi Rakieh and Ioannis Kanakis
Int. J. Mol. Sci. 2024, 25(14), 7988; https://doi.org/10.3390/ijms25147988 - 22 Jul 2024
Viewed by 731
Abstract
Diabetic bone disease (DBD) is a frequent complication in patients with type 2 diabetes mellitus (T2DM), characterised by altered bone mineral density (BMD) and bone turnover marker (BTMs) levels. The impact of different anti-diabetic medications on the skeleton remains unclear, and studies have [...] Read more.
Diabetic bone disease (DBD) is a frequent complication in patients with type 2 diabetes mellitus (T2DM), characterised by altered bone mineral density (BMD) and bone turnover marker (BTMs) levels. The impact of different anti-diabetic medications on the skeleton remains unclear, and studies have reported conflicting results; thus, the need for a comprehensive systematic review is of paramount importance. A systematic search was conducted in PubMed and the Cochrane Library. The primary outcomes assessed were changes in BMD in relation to different anatomical sites and BTMs, including mainly P1NP and CTX as well as OPG, OCN, B-ALP and RANK-L. Risk of bias was evaluated using the JADAD score. The meta-analysis of 19 randomised controlled trials comprising 4914 patients showed that anti-diabetic medications overall increased BMD at the lumbar spine (SMD: 0.93, 95% CI [0.13, 1.73], p = 0.02), femoral neck (SMD: 1.10, 95% CI [0.47, 1.74], p = 0.0007) and in total hip (SMD: 0.33, 95% CI [−0.25, 0.92], p = 0.27) in comparison with placebo, but when compared with metformin, the overall effect favoured metformin over other treatments (SMD: −0.23, 95% CI [−0.39, −0.07], p = 0.004). GLP-1 receptor agonists and insulin analogues seem to improve BMD compared to placebo, while SGLT2 inhibitors and thiazolidinediones (TZDs) showed no significant effect, although studies’ number cannot lead to safe conclusions. For BTMs, TZDs significantly increased P1NP levels compared to placebo. However, no significant differences were observed for CTX, B-ALP, OCN, OPG, and RANK-L between anti-diabetic drugs and metformin or placebo. High heterogeneity and diverse follow-up durations among studies were evident, which obscures the validity of the results. This review highlights the variable effects of anti-diabetic drugs on DBD in T2DM patients, emphasising the need for long-term trials with robust designs to better understand these relationships and inform clinical decisions. Full article
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<p>PRISMA flow diagram of the selection process for the included articles.</p>
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<p>Standardised mean differences in BMD measurements based on different anatomical sites in T2DM patients receiving different classes of anti-diabetic drugs versus placebo. SMD in subgroups as well as total effect are presented with 95% confidence intervals using the random effects model [<a href="#B36-ijms-25-07988" class="html-bibr">36</a>,<a href="#B44-ijms-25-07988" class="html-bibr">44</a>,<a href="#B46-ijms-25-07988" class="html-bibr">46</a>,<a href="#B48-ijms-25-07988" class="html-bibr">48</a>,<a href="#B50-ijms-25-07988" class="html-bibr">50</a>].</p>
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<p>Mean differences in BMD measurements based on different anatomical sites in T2DM patients receiving different classes of anti-diabetic drugs versus metformin. Mean differences in subgroups as well as total effect are presented with 95% confidence intervals using the random effects model [<a href="#B53-ijms-25-07988" class="html-bibr">53</a>,<a href="#B57-ijms-25-07988" class="html-bibr">57</a>,<a href="#B58-ijms-25-07988" class="html-bibr">58</a>,<a href="#B61-ijms-25-07988" class="html-bibr">61</a>].</p>
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<p>Mean differences in serum P1NP levels receiving various anti-diabetic drugs versus placebo. Mean differences in the studies as well as total effect are presented with 95% confidence intervals using the random effects model [<a href="#B36-ijms-25-07988" class="html-bibr">36</a>,<a href="#B45-ijms-25-07988" class="html-bibr">45</a>,<a href="#B46-ijms-25-07988" class="html-bibr">46</a>,<a href="#B47-ijms-25-07988" class="html-bibr">47</a>,<a href="#B48-ijms-25-07988" class="html-bibr">48</a>,<a href="#B50-ijms-25-07988" class="html-bibr">50</a>].</p>
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<p>SMD in serum P1NP levels in patients receiving various anti-diabetic drugs versus metformin. Meta-regression was performed by applying the random effects model [<a href="#B51-ijms-25-07988" class="html-bibr">51</a>,<a href="#B52-ijms-25-07988" class="html-bibr">52</a>,<a href="#B53-ijms-25-07988" class="html-bibr">53</a>,<a href="#B54-ijms-25-07988" class="html-bibr">54</a>].</p>
Full article ">Figure 6
<p>SMD in serum CTX levels comparing various anti-diabetic drugs versus placebo. Meta-regression was performed by applying the random effects model [<a href="#B36-ijms-25-07988" class="html-bibr">36</a>,<a href="#B45-ijms-25-07988" class="html-bibr">45</a>,<a href="#B46-ijms-25-07988" class="html-bibr">46</a>,<a href="#B47-ijms-25-07988" class="html-bibr">47</a>,<a href="#B48-ijms-25-07988" class="html-bibr">48</a>,<a href="#B50-ijms-25-07988" class="html-bibr">50</a>].</p>
Full article ">Figure 7
<p>SMD in serum CTX levels in the comparison of anti-diabetic drugs versus metformin. Meta-regression was performed using the random effects model [<a href="#B51-ijms-25-07988" class="html-bibr">51</a>,<a href="#B52-ijms-25-07988" class="html-bibr">52</a>,<a href="#B53-ijms-25-07988" class="html-bibr">53</a>,<a href="#B54-ijms-25-07988" class="html-bibr">54</a>].</p>
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