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Papaefthimiou M, Kontou PI, Bagos PG, Braliou GG. Integration of Antioxidant Activity Assays Data of Stevia Leaf Extracts: A Systematic Review and Meta-Analysis. Antioxidants (Basel) 2024; 13:692. [PMID: 38929131 PMCID: PMC11201069 DOI: 10.3390/antiox13060692] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/28/2024] [Revised: 05/22/2024] [Accepted: 05/28/2024] [Indexed: 06/28/2024] Open
Abstract
Stevia rebaudiana Bertoni, a no-calorie natural sweetener, contains a plethora of polyphenols that exert antioxidant properties with potential medicinal significance. Due to the variety of functional groups, polyphenols exhibit varying solubility depending on the nature of the extraction solvents (water, organic, or their mixtures, defined further on as hydroalcoholic extracts). In the present study, we performed a systematic review, following PRISMA guidelines, and meta-analysis, synthesizing all available data from 45 articles encompassing 250 different studies. Our results showed that the total phenolic content (TPC) of hydroalcoholic and aqueous extracts presents higher values (64.77 and 63.73 mg GAE/g) compared to organic extracts (33.39). Total flavonoid content (TFC) was also higher in aqueous and hydroalcoholic extracts; meta-regression analysis revealed that outcomes in different measuring units (mg QE/g, mg CE/g, and mg RUE/g) do not present statistically significant differences and can be synthesized in meta-analysis. Using meta-regression analysis, we showed that outcomes from the chemical-based ABTS, FRAP, and ORAC antioxidant assays for the same extract type can be combined in meta-analysis because they do not differ statistically significantly. Meta-analysis of ABTS, FRAP, and ORAC assays outcomes revealed that the antioxidant activity profile of various extract types follows that of their phenolic and flavonoid content. Using regression meta-analysis, we also presented that outcomes from SOD, CAT, and POX enzymatic antioxidant assays are independent of the assay type (p-value = 0.905) and can be combined. Our study constitutes the first effort to quantitatively and statistically synthesize the research results of individual studies using all methods measuring the antioxidant activity of stevia leaf extracts. Our results, in light of evidence-based practice, uncover the need for a broadly accepted, unified, methodological strategy to perform antioxidant tests, and offer documentation that the use of ethanol:water 1:1 mixtures or pure water can more efficiently extract stevia antioxidant compounds.
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Affiliation(s)
- Maria Papaefthimiou
- Department of Computer Science and Biomedical Informatics, University of Thessaly, 35131 Lamia, Greece; (M.P.); (P.G.B.)
| | | | - Pantelis G. Bagos
- Department of Computer Science and Biomedical Informatics, University of Thessaly, 35131 Lamia, Greece; (M.P.); (P.G.B.)
| | - Georgia G. Braliou
- Department of Computer Science and Biomedical Informatics, University of Thessaly, 35131 Lamia, Greece; (M.P.); (P.G.B.)
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2
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Sarafidis M, Lambrou GI, Zoumpourlis V, Koutsouris D. An Integrated Bioinformatics Analysis towards the Identification of Diagnostic, Prognostic, and Predictive Key Biomarkers for Urinary Bladder Cancer. Cancers (Basel) 2022; 14:cancers14143358. [PMID: 35884419 PMCID: PMC9319344 DOI: 10.3390/cancers14143358] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/08/2022] [Revised: 07/03/2022] [Accepted: 07/06/2022] [Indexed: 02/04/2023] Open
Abstract
Simple Summary Bladder cancer is evidently a challenge as far as its prognosis and treatment are concerned. The investigation of potential biomarkers and therapeutic targets is indispensable and still in progress. Most studies attempt to identify differential signatures between distinct molecular tumor subtypes. Therefore, keeping in mind the heterogeneity of urinary bladder tumors, we attempted to identify a consensus gene-related signature between the common expression profile of bladder cancer and control samples. In the quest for substantive features, we were able to identify key hub genes, whose signatures could hold diagnostic, prognostic, or therapeutic significance, but, primarily, could contribute to a better understanding of urinary bladder cancer biology. Abstract Bladder cancer (BCa) is one of the most prevalent cancers worldwide and accounts for high morbidity and mortality. This study intended to elucidate potential key biomarkers related to the occurrence, development, and prognosis of BCa through an integrated bioinformatics analysis. In this context, a systematic meta-analysis, integrating 18 microarray gene expression datasets from the GEO repository into a merged meta-dataset, identified 815 robust differentially expressed genes (DEGs). The key hub genes resulted from DEG-based protein–protein interaction and weighted gene co-expression network analyses were screened for their differential expression in urine and blood plasma samples of BCa patients. Subsequently, they were tested for their prognostic value, and a three-gene signature model, including COL3A1, FOXM1, and PLK4, was built. In addition, they were tested for their predictive value regarding muscle-invasive BCa patients’ response to neoadjuvant chemotherapy. A six-gene signature model, including ANXA5, CD44, NCAM1, SPP1, CDCA8, and KIF14, was developed. In conclusion, this study identified nine key biomarker genes, namely ANXA5, CDT1, COL3A1, SPP1, VEGFA, CDCA8, HJURP, TOP2A, and COL6A1, which were differentially expressed in urine or blood of BCa patients, held a prognostic or predictive value, and were immunohistochemically validated. These biomarkers may be of significance as prognostic and therapeutic targets for BCa.
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Affiliation(s)
- Michail Sarafidis
- Biomedical Engineering Laboratory, School of Electrical and Computer Engineering, National Technical University of Athens, 9 Iroon Polytechniou Str., 15780 Athens, Greece;
- Correspondence: ; Tel.: +30-210-772-2430
| | - George I. Lambrou
- Choremeio Research Laboratory, First Department of Pediatrics, National and Kapodistrian University of Athens, 8 Thivon & Levadeias Str., 11527 Athens, Greece;
- University Research Institute of Maternal and Child Health and Precision Medicine, National and Kapodistrian University of Athens, 8 Thivon & Levadeias Str., 11527 Athens, Greece
| | - Vassilis Zoumpourlis
- Biomedical Applications Unit, Institute of Chemical Biology, National Hellenic Research Foundation, 48 Vas. Konstantinou Ave., 11635 Athens, Greece;
| | - Dimitrios Koutsouris
- Biomedical Engineering Laboratory, School of Electrical and Computer Engineering, National Technical University of Athens, 9 Iroon Polytechniou Str., 15780 Athens, Greece;
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3
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Tamposis IA, Manios GA, Charitou T, Vennou KE, Kontou PI, Bagos PG. MAGE: An Open-Source Tool for Meta-Analysis of Gene Expression Studies. BIOLOGY 2022; 11:biology11060895. [PMID: 35741417 PMCID: PMC9220151 DOI: 10.3390/biology11060895] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 05/12/2022] [Revised: 06/05/2022] [Accepted: 06/08/2022] [Indexed: 11/16/2022]
Abstract
MAGE (Meta-Analysis of Gene Expression) is a Python open-source software package designed to perform meta-analysis and functional enrichment analysis of gene expression data. We incorporate standard methods for the meta-analysis of gene expression studies, bootstrap standard errors, corrections for multiple testing, and meta-analysis of multiple outcomes. Importantly, the MAGE toolkit includes additional features for the conversion of probes to gene identifiers, and for conducting functional enrichment analysis, with annotated results, of statistically significant enriched terms in several formats. Along with the tool itself, a web-based infrastructure was also developed to support the features of this package.
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Affiliation(s)
- Ioannis A. Tamposis
- Department of Computer Science and Biomedical Informatics, University of Thessaly, 35131 Lamia, Greece; (I.A.T.); (G.A.M.); (T.C.); (K.E.V.)
| | - Georgios A. Manios
- Department of Computer Science and Biomedical Informatics, University of Thessaly, 35131 Lamia, Greece; (I.A.T.); (G.A.M.); (T.C.); (K.E.V.)
| | - Theodosia Charitou
- Department of Computer Science and Biomedical Informatics, University of Thessaly, 35131 Lamia, Greece; (I.A.T.); (G.A.M.); (T.C.); (K.E.V.)
| | - Konstantina E. Vennou
- Department of Computer Science and Biomedical Informatics, University of Thessaly, 35131 Lamia, Greece; (I.A.T.); (G.A.M.); (T.C.); (K.E.V.)
| | | | - Pantelis G. Bagos
- Department of Computer Science and Biomedical Informatics, University of Thessaly, 35131 Lamia, Greece; (I.A.T.); (G.A.M.); (T.C.); (K.E.V.)
- Correspondence:
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4
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Goutzelas Y, Kontou P, Mamuris Z, Bagos P, Sarafidou T. Meta-analysis of gene expression data in adipose tissue reveals new obesity associated genes. Gene 2022; 818:146223. [PMID: 35063573 DOI: 10.1016/j.gene.2022.146223] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/11/2021] [Revised: 11/28/2021] [Accepted: 01/13/2022] [Indexed: 01/16/2023]
Abstract
High-throughput transcriptomic and proteomic data like microarray data are deposited in public databases such as Gene Expression Omnibus (GEO). Omics data integration and processing from different and independent studies is achieved by using efficient and effective computational tools through meta-analysis. Meta-analysis is a statistical powerful tool combining data from numerous studies, minimizes bias and increases statistical power by increasing sample size compared to individual studies. Therefore, we performed a meta-analysis of gene expression data in adipose tissue to identify genes that are differentially expressed between obese and non-obese subjects as well as to detect gene expression signatures, pathways and networks associated with obesity. We identified 821 differentially expressed genes (DEGs) in adipose tissue of obese subjects compared to non-obese. A protein-protein interactions (PPIs) network was reconstructed consisting of 168 proteins. Functional enrichment analysis in the network revealed proteins involved in RNA and energy metabolism. The KEGG pathway analysis revealed 15 enriched pathway terms. Furthermore, multiple testing correction methods identified five statistically significant obesity associated genes (NDUFA12, SFI1, SSB, FAR2 and LACE1) that require further investigation.
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Affiliation(s)
- Yiannis Goutzelas
- Department of Biochemistry and Biotechnology, University of Thessaly, Larissa, Greece
| | - Panagiota Kontou
- Department of Computer Science and Biomedical Informatics, University of Thessaly, Lamia, Greece
| | - Zissis Mamuris
- Department of Biochemistry and Biotechnology, University of Thessaly, Larissa, Greece
| | - Pantelis Bagos
- Department of Computer Science and Biomedical Informatics, University of Thessaly, Lamia, Greece
| | - Theologia Sarafidou
- Department of Biochemistry and Biotechnology, University of Thessaly, Larissa, Greece.
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5
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Gautam Y, Johansson E, Mersha TB. Multi-Omics Profiling Approach to Asthma: An Evolving Paradigm. J Pers Med 2022; 12:jpm12010066. [PMID: 35055381 PMCID: PMC8778153 DOI: 10.3390/jpm12010066] [Citation(s) in RCA: 27] [Impact Index Per Article: 13.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/24/2021] [Revised: 12/23/2021] [Accepted: 12/28/2021] [Indexed: 02/04/2023] Open
Abstract
Asthma is a complex multifactorial and heterogeneous respiratory disease. Although genetics is a strong risk factor of asthma, external and internal exposures and their interactions with genetic factors also play important roles in the pathophysiology of asthma. Over the past decades, the application of high-throughput omics approaches has emerged and been applied to the field of asthma research for screening biomarkers such as genes, transcript, proteins, and metabolites in an unbiased fashion. Leveraging large-scale studies representative of diverse population-based omics data and integrating with clinical data has led to better profiling of asthma risk. Yet, to date, no omic-driven endotypes have been translated into clinical practice and management of asthma. In this article, we provide an overview of the current status of omics studies of asthma, namely, genomics, transcriptomics, epigenomics, proteomics, exposomics, and metabolomics. The current development of the multi-omics integrations of asthma is also briefly discussed. Biomarker discovery following multi-omics profiling could be challenging but useful for better disease phenotyping and endotyping that can translate into advances in asthma management and clinical care, ultimately leading to successful precision medicine approaches.
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Toy HI, Karakülah G, Kontou PI, Alotaibi H, Georgakilas AG, Pavlopoulou A. Investigating Molecular Determinants of Cancer Cell Resistance to Ionizing Radiation Through an Integrative Bioinformatics Approach. Front Cell Dev Biol 2021; 9:620248. [PMID: 33898418 PMCID: PMC8058375 DOI: 10.3389/fcell.2021.620248] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/22/2020] [Accepted: 03/15/2021] [Indexed: 12/13/2022] Open
Abstract
Eradication of cancer cells through exposure to high doses of ionizing radiation (IR) is a widely used therapeutic strategy in the clinical setting. However, in many cases, cancer cells can develop remarkable resistance to radiation. Radioresistance represents a prominent obstacle in the effective treatment of cancer. Therefore, elucidation of the molecular mechanisms and pathways related to radioresistance in cancer cells is of paramount importance. In the present study, an integrative bioinformatics approach was applied to three publicly available RNA sequencing and microarray transcriptome datasets of human cancer cells of different tissue origins treated with ionizing radiation. These data were investigated in order to identify genes with a significantly altered expression between radioresistant and corresponding radiosensitive cancer cells. Through rigorous statistical and biological analyses, 36 genes were identified as potential biomarkers of radioresistance. These genes, which are primarily implicated in DNA damage repair, oxidative stress, cell pro-survival, and apoptotic pathways, could serve as potential diagnostic/prognostic markers cancer cell resistance to radiation treatment, as well as for therapy outcome and cancer patient survival. In addition, our findings could be potentially utilized in the laboratory and clinical setting for enhancing cancer cell susceptibility to radiation therapy protocols.
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Affiliation(s)
- Halil Ibrahim Toy
- Izmir Biomedicine and Genome Center, Izmir, Turkey.,Izmir International Biomedicine and Genome Institute, Dokuz Eylül University, Izmir, Turkey
| | - Gökhan Karakülah
- Izmir Biomedicine and Genome Center, Izmir, Turkey.,Izmir International Biomedicine and Genome Institute, Dokuz Eylül University, Izmir, Turkey
| | - Panagiota I Kontou
- Department of Computer Science and Biomedical Informatics, University of Thessaly, Lamia, Greece
| | - Hani Alotaibi
- Izmir Biomedicine and Genome Center, Izmir, Turkey.,Izmir International Biomedicine and Genome Institute, Dokuz Eylül University, Izmir, Turkey
| | - Alexandros G Georgakilas
- DNA Damage Laboratory, Department of Physics, School of Applied Mathematical and Physical Sciences, Zografou, National Technical University of Athens, Athens, Greece
| | - Athanasia Pavlopoulou
- Izmir Biomedicine and Genome Center, Izmir, Turkey.,Izmir International Biomedicine and Genome Institute, Dokuz Eylül University, Izmir, Turkey
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Mentis AFA, Dardiotis E, Chrousos GP. Apolipoprotein E4 and meningeal lymphatics in Alzheimer disease: a conceptual framework. Mol Psychiatry 2021; 26:1075-1097. [PMID: 32355332 PMCID: PMC7985019 DOI: 10.1038/s41380-020-0731-7] [Citation(s) in RCA: 39] [Impact Index Per Article: 13.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/03/2019] [Revised: 04/01/2020] [Accepted: 04/09/2020] [Indexed: 12/11/2022]
Abstract
The potential existence and roles of the meningeal lymphatic system in normal and pathological brain function have been a long-standing enigma. Recent evidence suggests that meningeal lymphatic vessels are present in both the mouse and human brain; in mice, they seem to play a role in clearing toxic amyloid-beta peptides, which have been connected with Alzheimer disease (AD). Here, we review the evidence linking the meningeal lymphatic system with human AD. Novel findings suggest that the recently described meningeal lymphatic vessels could be linked to, and possibly drain, the efferent paravascular glial lymphatic (glymphatic) system carrying cerebrospinal fluid, after solute and immune cell exchange with brain interstitial fluid. In so doing, the glymphatic system could contribute to the export of toxic solutes and immune cells from the brain (an exported fluid we wish to describe as glymph, similarly to lymph) to the meningeal lymphatic system; the latter, by being connected with downstream anatomic regions, carries the glymph to the conventional cervical lymphatic vessels and nodes. Thus, abnormal function in the meningeal lymphatic system could, in theory, lead to the accumulation, in the brain, of amyloid-beta, cellular debris, and inflammatory mediators, as well as immune cells, resulting in damage of the brain parenchyma and, in turn, cognitive and other neurologic dysfunctions. In addition, we provide novel insights into APOE4-the leading genetic risk factor for AD-and its relation to the meningeal lymphatic system. In this regard, we have reanalyzed previously published RNA-Seq data to show that induced pluripotent stem cells (iPSCs) carrying the APOE4 allele (either as APOE4 knock-in or stemming from APOE4 patients) express lower levels of (a) genes associated with lymphatic markers, and (b) genes for which well-characterized missense mutations have been linked to peripheral lymphedema. Taking into account this evidence, we propose a new conceptual framework, according to which APOE4 could play a novel role in the premature shrinkage of meningeal lymphatic vessels (meningeal lymphosclerosis), leading to abnormal meningeal lymphatic functions (meningeal lymphedema), and, in turn, reduction in the clearance of amyloid-beta and other macromolecules and inflammatory mediators, as well as immune cells, from the brain, exacerbation of AD manifestations, and progression of the disease. Altogether, these findings and their potential interpretations may herald novel diagnostic tools and therapeutic approaches in patients with AD.
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Affiliation(s)
- Alexios-Fotios A Mentis
- Public Health Laboratories, Hellenic Pasteur Institute, Vas. Sofias Avenue 127, 115 21, Athens, Greece.
- Department of Microbiology, University of Thessaly, Panepistimiou 3, Viopolis, 41 500, Larissa, Greece.
| | - Efthimios Dardiotis
- Department of Neurology, University of Thessaly, Panepistimiou 3, Viopolis, 41 500, Larissa, Greece
| | - George P Chrousos
- University Research Institute of Maternal and Child Health and Precision Medicine, National and Kapodistrian University of Athens, Medical School, Aghia Sophia Children's Hospital, Livadias 8, 115 27, Athens, Greece
- UNESCO Chair on Adolescent Health Care, Athens, Greece
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8
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Park HW, Weiss ST. Understanding the Molecular Mechanisms of Asthma through Transcriptomics. ALLERGY, ASTHMA & IMMUNOLOGY RESEARCH 2020; 12:399-411. [PMID: 32141255 PMCID: PMC7061151 DOI: 10.4168/aair.2020.12.3.399] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 11/08/2019] [Revised: 01/01/2020] [Accepted: 01/11/2020] [Indexed: 12/18/2022]
Abstract
The transcriptome represents the complete set of RNA transcripts that are produced by the genome under a specific circumstance or in a specific cell. High-throughput methods, including microarray and bulk RNA sequencing, as well as recent advances in biostatistics based on machine learning approaches provides a quick and effective way of identifying novel genes and pathways related to asthma, which is a heterogeneous disease with diverse pathophysiological mechanisms. In this manuscript, we briefly review how to analyze transcriptome data and then provide a summary of recent transcriptome studies focusing on asthma pathogenesis and asthma drug responses. Studies reviewed here are classified into 2 classes based on the tissues utilized: blood and airway cells.
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Affiliation(s)
- Heung Woo Park
- The Channing Division of Network Medicine, Department of Medicine, Brigham & Women's Hospital and Harvard Medical School, Boston, MA, USA.,Department of Internal Medicine, Seoul National University College of Medicine, Seoul, Korea
| | - Scott T Weiss
- The Channing Division of Network Medicine, Department of Medicine, Brigham & Women's Hospital and Harvard Medical School, Boston, MA, USA.,Partners Center for Personalized Medicine, Partners Health Care, Boston, MA, USA.
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Forero DA. Available Software for Meta-analyses of Genome-wide Expression Studies. Curr Genomics 2019; 20:325-331. [PMID: 32476989 PMCID: PMC7235394 DOI: 10.2174/1389202920666190822113912] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/24/2019] [Revised: 07/24/2019] [Accepted: 08/08/2019] [Indexed: 01/24/2023] Open
Abstract
Advances in transcriptomic methods have led to a large number of published Genome-Wide Expression Studies (GWES), in humans and model organisms. For several years, GWES involved the use of microarray platforms to compare genome-expression data for two or more groups of samples of interest. Meta-analysis of GWES is a powerful approach for the identification of differentially expressed genes in biological topics or diseases of interest, combining information from multiple primary studies. In this article, the main features of available software for carrying out meta-analysis of GWES have been reviewed and seven packages from the Bioconductor platform and five packages from the CRAN platform have been described. In addition, nine previously described programs and four online programs are reviewed. Finally, advantages and disadvantages of these available programs and proposed key points for future developments have been discussed.
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Affiliation(s)
- Diego A Forero
- PhD Program in Health Sciences, School of Medicine, Universidad Antonio Nariño, Bogotá, Colombia.,Laboratory of NeuroPsychiatric Genetics, Biomedical Sciences Research Group, School of Medicine, Universidad Antonio Nariño, Bogotá, Colombia
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Forero DA, González-Giraldo Y. Convergent functional genomics of cocaine misuse in humans and animal models. THE AMERICAN JOURNAL OF DRUG AND ALCOHOL ABUSE 2019; 46:22-30. [DOI: 10.1080/00952990.2019.1636384] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/07/2023]
Affiliation(s)
- Diego A. Forero
- Laboratory of NeuroPsychiatric Genetics, Biomedical Sciences Research Group, School of Medicine, Universidad Antonio Nariño, Bogotá, Colombia
- Health Sciences, School of Medicine, Universidad Antonio Nariño, Bogotá, Colombia
| | - Yeimy González-Giraldo
- Departamento de Nutrición y Bioquímica, Facultad de Ciencias, Pontificia Universidad Javeriana, Bogotá, Colombia
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