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Chatatikun M, Tedasen A, Phinyo P, Wongyikul P, Klangbud WK, Kawakami F, Imai M, Chuaijit S, Rachmuangfang S, Phuwarinyodsakul S, Leelawattana R, Phongphithakchai A. Hypoglycemic activity of Garcinia mangostana L. extracts on diabetes rodent models: A systematic review and network meta-analysis. Front Pharmacol 2024; 15:1472419. [PMID: 39415841 PMCID: PMC11479905 DOI: 10.3389/fphar.2024.1472419] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/29/2024] [Accepted: 09/05/2024] [Indexed: 10/19/2024] Open
Abstract
Background Diabetes mellitus is a significant global health issue, and alternative treatments from natural products like Garcinia mangostana L. [Clusiaceae] or GM are being explored for their potential benefits. This study focused on evaluating the hypoglycemic effects of GM on diabetic rodent models. Methods A comprehensive search was conducted in PubMed, Scopus, and Embase for studies reporting blood glucose levels within 2 weeks as the primary outcome and changes in total cholesterol (TC), triglycerides (TG), low-density lipoprotein cholesterol (LDL-C), and high-density lipoprotein cholesterol (HDL-C) as secondary outcomes. A network meta-analysis (NMA) was performed to determine the pooled effectiveness of each intervention, estimating the weighted mean difference (WMD) and 95% confidence interval (CI) from both direct and indirect evidence. The surface under the cumulative ranking curve (SURCA) was used to rank the interventions. Results Ten articles were identified, with nine included for quantitative analysis. All GM extracts showed greater effectiveness than the control in decreasing blood glucose levels within 2 weeks. GM at 200 mg/kg (GM200) was the top-ranked extract for reducing glucose levels beyond 2 weeks and increasing HDL-C levels. The ethanol extract of GM at 200 mg/kg (GME200) was the most effective for blood glucose reduction within 2 weeks and for TC and TG reductions. The methanol extract of GM at 200 mg/kg (GMM200) was the top-ranked extract for LDL-C reductions. Conclusion GM and its extracts demonstrated significant hypoglycemic activity and improvements in lipid profiles in diabetic rodent models, highlighting their potential as therapeutic agents for the prevention and treatment of diabetes mellitus. Further research in human trials is warranted to confirm these findings and establish clinical applications. Clinical trial registration https://www.crd.york.ac.uk/prospero/display_record.php?ID=CRD42023426254.
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Affiliation(s)
- Moragot Chatatikun
- Department of Medical Technology, School of Allied Health Sciences, Walailak University, Nakhon Si Thammarat, Thailand
- Center of Excellence Research for Melioidosis and Microorganisms (CERMM), Walailak University, Nakhon Si Thammarat, Thailand
| | - Aman Tedasen
- Department of Medical Technology, School of Allied Health Sciences, Walailak University, Nakhon Si Thammarat, Thailand
- Research Excellence Center for Innovation and Health Products (RECIHP), Walailak University, Nakhon Si Thammarat, Thailand
| | - Phichayut Phinyo
- Center for Clinical Epidemiology and Clinical Statistics, Department of Biomedical Informatics and Clinical Epidemiology (BioCE), Faculty of Medicine, Chiang Mai University, Chiang Mai, Thailand
| | - Pakpoom Wongyikul
- Center for Clinical Epidemiology and Clinical Statistics, Department of Biomedical Informatics and Clinical Epidemiology (BioCE), Faculty of Medicine, Chiang Mai University, Chiang Mai, Thailand
| | - Wiyada Kwanhian Klangbud
- Medical Technology program, Faculty of Science, Nakhon Phanom University, Nakhon Phanom, Thailand
| | - Fumitaka Kawakami
- Research Facility of Regenerative Medicine and Cell Design, School of Allied Health Sciences, Kitasato University, Sagamihara, Japan
- Department of Regulation Biochemistry, Kitasato University Graduate School of Medical Sciences, Sagamihara, Japan
| | - Motoki Imai
- Research Facility of Regenerative Medicine and Cell Design, School of Allied Health Sciences, Kitasato University, Sagamihara, Japan
- Department of Molecular Diagnostics, School of Allied Health Sciences, Kitasato University, Sagamihara, Japan
| | - Sirithip Chuaijit
- Department of Medical Science, School of Medicine, Walailak University, Nakhon Si Thammarat, Thailand
| | - Sarawut Rachmuangfang
- Department of Medical Technology, School of Allied Health Sciences, Walailak University, Nakhon Si Thammarat, Thailand
| | - Siriporn Phuwarinyodsakul
- Department of Medical Technology, School of Allied Health Sciences, Walailak University, Nakhon Si Thammarat, Thailand
| | - Rattana Leelawattana
- Endocrinology and Metabolism Unit, Division of Internal Medicine, Faculty of Medicine, Prince of Songkla University, Songkhla, Thailand
| | - Atthaphong Phongphithakchai
- Nephrology Unit, Division of Internal Medicine, Faculty of Medicine, Prince of Songkla University, Songkhla, Thailand
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Matchado MS, Rühlemann M, Reitmeier S, Kacprowski T, Frost F, Haller D, Baumbach J, List M. On the limits of 16S rRNA gene-based metagenome prediction and functional profiling. Microb Genom 2024; 10:001203. [PMID: 38421266 PMCID: PMC10926695 DOI: 10.1099/mgen.0.001203] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/24/2023] [Accepted: 02/05/2024] [Indexed: 03/02/2024] Open
Abstract
Molecular profiling techniques such as metagenomics, metatranscriptomics or metabolomics offer important insights into the functional diversity of the microbiome. In contrast, 16S rRNA gene sequencing, a widespread and cost-effective technique to measure microbial diversity, only allows for indirect estimation of microbial function. To mitigate this, tools such as PICRUSt2, Tax4Fun2, PanFP and MetGEM infer functional profiles from 16S rRNA gene sequencing data using different algorithms. Prior studies have cast doubts on the quality of these predictions, motivating us to systematically evaluate these tools using matched 16S rRNA gene sequencing, metagenomic datasets, and simulated data. Our contribution is threefold: (i) using simulated data, we investigate if technical biases could explain the discordance between inferred and expected results; (ii) considering human cohorts for type two diabetes, colorectal cancer and obesity, we test if health-related differential abundance measures of functional categories are concordant between 16S rRNA gene-inferred and metagenome-derived profiles and; (iii) since 16S rRNA gene copy number is an important confounder in functional profiles inference, we investigate if a customised copy number normalisation with the rrnDB database could improve the results. Our results show that 16S rRNA gene-based functional inference tools generally do not have the necessary sensitivity to delineate health-related functional changes in the microbiome and should thus be used with care. Furthermore, we outline important differences in the individual tools tested and offer recommendations for tool selection.
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Affiliation(s)
- Monica Steffi Matchado
- Data Science in Systems Biology, TUM School of Life Sciences, Technical University of Munich, Freising, Germany
- Institute for Computational Systems Biology, University of Hamburg, Hamburg, Germany
| | - Malte Rühlemann
- Institute of Clinical Molecular Biology, Kiel University, Kiel, Germany
| | - Sandra Reitmeier
- ZIEL - Institute for Food & Health, Core Facility Microbiome, Technical University of Munich, Freising, Germany
| | - Tim Kacprowski
- Division Data Science in Biomedicine, Peter L. Reichertz Institute for Medical Informatics of Technische Universität Braunschweig and Hannover Medical School, Braunschweig, Germany
- Braunschweig Integrated Centre of Systems Biology (BRICS), TU Braunschweig, Braunschweig, Germany
- Department of Computational Biology of Infection Research, Helmholtz Centre for Infection Research (HZI), Braunschweig, Germany
| | - Fabian Frost
- Department of Medicine A, University Medicine Greifswald, Greifswald, Germany
| | - Dirk Haller
- ZIEL - Institute for Food & Health, Core Facility Microbiome, Technical University of Munich, Freising, Germany
- Chair of Nutrition and Immunology, TUM School of Life Sciences, Technical University of Munich, Freising, Germany
| | - Jan Baumbach
- Institute for Computational Systems Biology, University of Hamburg, Hamburg, Germany
- Institute of Mathematics and Computer Science, University of Southern Denmark, Odense, Denmark
| | - Markus List
- Data Science in Systems Biology, TUM School of Life Sciences, Technical University of Munich, Freising, Germany
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and Alternative Medicine EBC. Retracted: Type 2 Diabetes Mellitus (T2DM) and Carbohydrate Metabolism in Relation to T2DM from Endocrinology, Neurophysiology, Molecular Biology, and Biochemistry Perspectives. EVIDENCE-BASED COMPLEMENTARY AND ALTERNATIVE MEDICINE : ECAM 2023; 2023:9849378. [PMID: 37501880 PMCID: PMC10371577 DOI: 10.1155/2023/9849378] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/18/2023] [Accepted: 07/18/2023] [Indexed: 07/29/2023]
Abstract
[This retracts the article DOI: 10.1155/2022/1708769.].
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Alfaqih MA, Aljanabi M, Ababneh E, Khanfar M, Alqudah M, Sater M. Leptin and the rs2167270 Polymorphism Are Associated with Glycemic Control in Type Two Diabetes Mellitus Patients on Metformin Therapy. MEDICINA (KAUNAS, LITHUANIA) 2023; 59:997. [PMID: 37241229 PMCID: PMC10221967 DOI: 10.3390/medicina59050997] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/13/2023] [Revised: 05/04/2023] [Accepted: 05/06/2023] [Indexed: 05/28/2023]
Abstract
Background and Objectives: Type two diabetes mellitus (T2DM) is a chronic disease with debilitating complications and high mortality. Evidence indicates that good glycemic control delays disease progression and is hence a target of disease management protocols. Nonetheless, some patients cannot maintain glycemic control. This study aimed to investigate the association between serum leptin levels and several SNPs of the LEP gene with the lack of glycemic control in T2DM patients on metformin therapy. Materials and Methods: In a hospital-based case-control study, 170 patients with poor glycemic control and 170 patients with good glycemic control were recruited. Serum leptin was measured. Patients were genotyped for three SNPs in the LEP gene (rs7799039, rs2167270, and rs791620). Results: Serum leptin was significantly lower in T2DM patients with poor glycemic control (p < 0.05). In multivariate analysis, serum leptin levels significantly lowered the risk of having poor glycemic control (OR = 0.985; CI: 0.976-0.994; p = 0.002); moreover, the GA genotype of rs2167270 was protective against poor glycemic control compared to the GG genotype (OR = 0.417; CI: 0.245-0.712; p = 0.001). Conclusions: Higher serum leptin and the GA genotype of the rs2167270 SNP of the LEP gene were associated with good glycemic control in T2DM patients on metformin therapy. Further studies with a larger sample size from multiple institutions are required to validate the findings.
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Affiliation(s)
- Mahmoud A. Alfaqih
- Department of Biochemistry, College of Medicine and Medical Sciences, Arabian Gulf University, Manama 15503, Bahrain;
- Department of Physiology and Biochemistry, Faculty of Medicine, Jordan University of Science and Technology, Irbid 22110, Jordan; (M.A.); (E.A.); (M.K.)
| | - Mukhallad Aljanabi
- Department of Physiology and Biochemistry, Faculty of Medicine, Jordan University of Science and Technology, Irbid 22110, Jordan; (M.A.); (E.A.); (M.K.)
| | - Ebaa Ababneh
- Department of Physiology and Biochemistry, Faculty of Medicine, Jordan University of Science and Technology, Irbid 22110, Jordan; (M.A.); (E.A.); (M.K.)
| | - Mariam Khanfar
- Department of Physiology and Biochemistry, Faculty of Medicine, Jordan University of Science and Technology, Irbid 22110, Jordan; (M.A.); (E.A.); (M.K.)
| | - Mohammad Alqudah
- Department of Physiology, Faculty of Medicine, College of Medicine and Medical Sciences, Manama 15503, Bahrain;
| | - Mai Sater
- Department of Biochemistry, College of Medicine and Medical Sciences, Arabian Gulf University, Manama 15503, Bahrain;
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Jarab AS, Al-Qerem W, Alqudah S, Abu Heshmeh SR, Mukattash TL, Alzoubi KH. Blood pressure control and its associated factors in patients with hypertension and type 2 diabetes. ELECTRONIC JOURNAL OF GENERAL MEDICINE 2023. [DOI: 10.29333/ejgm/13028] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/07/2023]
Abstract
In this retrospective study, the medical records of hypertensive patients with type 2 diabetes attending two major hospitals were reviewed to find the factors associated with poor blood pressure control in patients who have diabetes as a comorbid disease with hypertension. Binary regression analysis was conducted to find the factors independently associated with BP control. A total of 522 participants were included in the study. Most of the participants had uncontrolled hypertension (63.4%) and uncontrolled type 2 diabetes (51.3%). Regression results revealed that having retinopathy (OR=1.468 (95% CI: 1.020-2.113), p<0.05), and not receiving dipeptidyl-peptidase 4 (DPP4) inhibitors were independently associated with uncontrolled BP (OR=0.633 (95%CI 0.423-0.946), p<0.05). Therefore, greater efforts should be exerted to improve BP control in hypertensive patients with type 2 diabetes, particularly in those suffering from retinopathy.
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Affiliation(s)
- Anan S Jarab
- College of Pharmacy, Al Ain University, Abu Dhabi, UAE
- Department of Clinical Pharmacy, Jordan University of Science and Technology, Irbid, JORDAN
| | - Walid Al-Qerem
- Department of Pharmacy, Al-Zaytoonah University of Jordan, Amman, JORDAN
| | - Salam Alqudah
- Department of Pharmacy, Jordanian Royal Medical Services, Amman, JORDAN
| | - Shrouq R Abu Heshmeh
- Department of Clinical Pharmacy, Jordan University of Science and Technology, Irbid, JORDAN
| | - Tareq L Mukattash
- Department of Clinical Pharmacy, Jordan University of Science and Technology, Irbid, JORDAN
| | - Karem H Alzoubi
- Department of Pharmacy Practice and Pharmacotherapeutics, University of Sharjah, Sharjah, UAE
- Faculty of Pharmacy, Jordan University of Science and Technology, Irbid, JORDAN
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