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Du L, Zong Y, Li H, Wang Q, Xie L, Yang B, Pang Y, Zhang C, Zhong Z, Gao J. Hyperuricemia and its related diseases: mechanisms and advances in therapy. Signal Transduct Target Ther 2024; 9:212. [PMID: 39191722 DOI: 10.1038/s41392-024-01916-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/03/2024] [Revised: 06/08/2024] [Accepted: 06/27/2024] [Indexed: 08/29/2024] Open
Abstract
Hyperuricemia, characterized by elevated levels of serum uric acid (SUA), is linked to a spectrum of commodities such as gout, cardiovascular diseases, renal disorders, metabolic syndrome, and diabetes, etc. Significantly impairing the quality of life for those affected, the prevalence of hyperuricemia is an upward trend globally, especially in most developed countries. UA possesses a multifaceted role, such as antioxidant, pro-oxidative, pro-inflammatory, nitric oxide modulating, anti-aging, and immune effects, which are significant in both physiological and pathological contexts. The equilibrium of circulating urate levels hinges on the interplay between production and excretion, a delicate balance orchestrated by urate transporter functions across various epithelial tissues and cell types. While existing research has identified hyperuricemia involvement in numerous biological processes and signaling pathways, the precise mechanisms connecting elevated UA levels to disease etiology remain to be fully elucidated. In addition, the influence of genetic susceptibilities and environmental determinants on hyperuricemia calls for a detailed and nuanced examination. This review compiles data from global epidemiological studies and clinical practices, exploring the physiological processes and the genetic foundations of urate transporters in depth. Furthermore, we uncover the complex mechanisms by which the UA induced inflammation influences metabolic processes in individuals with hyperuricemia and the association with its relative disease, offering a foundation for innovative therapeutic approaches and advanced pharmacological strategies.
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Grants
- 82002339, 81820108020 National Natural Science Foundation of China (National Science Foundation of China)
- 82002339, 81820108020 National Natural Science Foundation of China (National Science Foundation of China)
- 82002339, 81820108020 National Natural Science Foundation of China (National Science Foundation of China)
- 82002339, 81820108020 National Natural Science Foundation of China (National Science Foundation of China)
- 82002339, 81820108020 National Natural Science Foundation of China (National Science Foundation of China)
- 82002339, 81820108020 National Natural Science Foundation of China (National Science Foundation of China)
- 82002339, 81820108020 National Natural Science Foundation of China (National Science Foundation of China)
- 82002339, 81820108020 National Natural Science Foundation of China (National Science Foundation of China)
- 82002339, 81820108020 National Natural Science Foundation of China (National Science Foundation of China)
- 82002339, 81820108020 National Natural Science Foundation of China (National Science Foundation of China)
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Affiliation(s)
- Lin Du
- Sports Medicine Center, The First Affiliated Hospital of Shantou University Medical College, Shantou, 515041, China
- Institute of Sports Medicine, Shantou University Medical College, Shantou, 515041, China
| | - Yao Zong
- Centre for Orthopaedic Research, Medical School, The University of Western Australia, Nedlands, WA, 6009, Australia
| | - Haorui Li
- Sports Medicine Center, The First Affiliated Hospital of Shantou University Medical College, Shantou, 515041, China
- Institute of Sports Medicine, Shantou University Medical College, Shantou, 515041, China
| | - Qiyue Wang
- Sports Medicine Center, The First Affiliated Hospital of Shantou University Medical College, Shantou, 515041, China
- Institute of Sports Medicine, Shantou University Medical College, Shantou, 515041, China
| | - Lei Xie
- Sports Medicine Center, The First Affiliated Hospital of Shantou University Medical College, Shantou, 515041, China
- Institute of Sports Medicine, Shantou University Medical College, Shantou, 515041, China
| | - Bo Yang
- Sports Medicine Center, The First Affiliated Hospital of Shantou University Medical College, Shantou, 515041, China
- Institute of Sports Medicine, Shantou University Medical College, Shantou, 515041, China
| | - Yidan Pang
- Department of Orthopaedics, Shanghai Sixth People's Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, 200233, China
| | - Changqing Zhang
- Department of Orthopaedics, Shanghai Sixth People's Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, 200233, China.
| | - Zhigang Zhong
- Sports Medicine Center, The First Affiliated Hospital of Shantou University Medical College, Shantou, 515041, China.
- Institute of Sports Medicine, Shantou University Medical College, Shantou, 515041, China.
| | - Junjie Gao
- Sports Medicine Center, The First Affiliated Hospital of Shantou University Medical College, Shantou, 515041, China.
- Institute of Sports Medicine, Shantou University Medical College, Shantou, 515041, China.
- Department of Orthopaedics, Shanghai Sixth People's Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, 200233, China.
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Lecona OA, Arroyo-Valerio AG, Bueno-Hernández N, Carrillo-Ruíz JD, Ruelas L, Márquez-Franco R, Aguado-García A, Barrón EV, Escobedo G, Ibarra-Coronado E, Olguín-Rodríguez PV, Barajas-Martínez A, Rivera AL, Fossion R. Risk factors contributing to infection with SARS-CoV-2 are modulated by sex. PLoS One 2024; 19:e0297901. [PMID: 38416704 PMCID: PMC10901358 DOI: 10.1371/journal.pone.0297901] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/07/2023] [Accepted: 01/15/2024] [Indexed: 03/01/2024] Open
Abstract
Throughout the early stages of the COVID-19 pandemic in Mexico (August-December 2020), we closely followed a cohort of n = 100 healthcare workers. These workers were initially seronegative for Immunoglobulin G (IgG) antibodies against SARS-CoV-2, the virus that causes COVID-19, and maintained close contact with patients afflicted by the disease. We explored the database of demographic, physiological and laboratory parameters of the cohort recorded at baseline to identify potential risk factors for infection with SARS-CoV-2 at a follow-up evaluation six months later. Given that susceptibility to infection may be a systemic rather than a local property, we hypothesized that a multivariate statistical analysis, such as MANOVA, may be an appropriate statistical approach. Our results indicate that susceptibility to infection with SARS-CoV-2 is modulated by sex. For men, different physiological states appear to exist that predispose to or protect against infection, whereas for women, we did not find evidence for divergent physiological states. Intriguingly, male participants who remained uninfected throughout the six-month observation period, had values for mean arterial pressure and waist-to-hip ratio that exceeded the normative reference range. We hypothesize that certain risk factors that worsen the outcome of COVID-19 disease, such as being overweight or having high blood pressure, may instead offer some protection against infection with SARS-CoV-2.
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Affiliation(s)
- Octavio A. Lecona
- Doctorado en Ciencias Biomédicas, Universidad Nacional Autónoma de México (UNAM), Mexico City, Mexico
- Centro de Ciencias de la Complejidad (C3), Universidad Nacional Autónoma de México (UNAM), Mexico City, Mexico
| | | | - Nallely Bueno-Hernández
- Dirección de Investigación, Hospital General de México Dr. Eduardo Liceaga, Mexico City, Mexico
| | - José Damian Carrillo-Ruíz
- Dirección de Investigación, Hospital General de México Dr. Eduardo Liceaga, Mexico City, Mexico
- Coordinación de Neurociencias, Facultad de Psicología, Universidad Anahuac México, Mexico City, Mexico
| | - Luis Ruelas
- Doctorado en Ciencias Biomédicas, Universidad Nacional Autónoma de México (UNAM), Mexico City, Mexico
- Centro de Ciencias de la Complejidad (C3), Universidad Nacional Autónoma de México (UNAM), Mexico City, Mexico
| | - René Márquez-Franco
- Doctorado en Ciencias Biomédicas, Universidad Nacional Autónoma de México (UNAM), Mexico City, Mexico
- Centro de Ciencias de la Complejidad (C3), Universidad Nacional Autónoma de México (UNAM), Mexico City, Mexico
| | - Alejandro Aguado-García
- Dirección de Investigación, Hospital General de México Dr. Eduardo Liceaga, Mexico City, Mexico
- Centro de Investigación en Ciencias (CInC), Universidad Autónoma del Estado de Morelos, Cuernavaca, Morelos, Mexico
| | - Eira Valeria Barrón
- Servicio de Medicina Genómica “Hospital General de México Dr. Eduardo Liceaga, Mexico City, Mexico
| | - Galileo Escobedo
- Dirección de Investigación, Hospital General de México Dr. Eduardo Liceaga, Mexico City, Mexico
| | - Elizabeth Ibarra-Coronado
- Centro de Ciencias de la Complejidad (C3), Universidad Nacional Autónoma de México (UNAM), Mexico City, Mexico
- Facultad de Medicina, Universidad Nacional Autónoma de México, Mexico City, Mexico
| | - Paola V. Olguín-Rodríguez
- Centro de Ciencias de la Complejidad (C3), Universidad Nacional Autónoma de México (UNAM), Mexico City, Mexico
- Centro de Investigación en Ciencias (CInC), Universidad Autónoma del Estado de Morelos, Cuernavaca, Morelos, Mexico
| | - Antonio Barajas-Martínez
- Centro de Ciencias de la Complejidad (C3), Universidad Nacional Autónoma de México (UNAM), Mexico City, Mexico
- Facultad de Medicina, Universidad Nacional Autónoma de México, Mexico City, Mexico
| | - Ana Leonor Rivera
- Centro de Ciencias de la Complejidad (C3), Universidad Nacional Autónoma de México (UNAM), Mexico City, Mexico
- Instituto de Ciencias Nucleares, Universidad Nacional Autónoma de México, Mexico City, Mexico
| | - Ruben Fossion
- Centro de Ciencias de la Complejidad (C3), Universidad Nacional Autónoma de México (UNAM), Mexico City, Mexico
- Instituto de Ciencias Nucleares, Universidad Nacional Autónoma de México, Mexico City, Mexico
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Nakazato Y, Shimoyama M, Cohen AA, Watanabe A, Kobayashi H, Shimoyama H, Shimoyama H. Intercorrelated variability in blood and hemodynamic biomarkers reveals physiological network in hemodialysis patients. Sci Rep 2023; 13:1660. [PMID: 36717578 PMCID: PMC9886931 DOI: 10.1038/s41598-023-28345-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/17/2022] [Accepted: 01/17/2023] [Indexed: 01/31/2023] Open
Abstract
Increased intra-individual variability of a variety of biomarkers is generally associated with poor health and reflects physiological dysregulation. Correlations among these biomarker variabilities should then represent interactions among heterogeneous biomarker regulatory systems. Herein, in an attempt to elucidate the network structure of physiological systems, we probed the inter-variability correlations of 22 biomarkers. Time series data on 19 blood-based and 3 hemodynamic biomarkers were collected over a one-year period for 334 hemodialysis patients, and their variabilities were evaluated by coefficients of variation. The network diagram exhibited six clusters in the physiological systems, corresponding to the regulatory domains for metabolism, inflammation, circulation, liver, salt, and protein. These domains were captured as latent factors in exploratory and confirmatory factor analyses (CFA). The 6-factor CFA model indicates that dysregulation in each of the domains manifests itself as increased variability in a specific set of biomarkers. Comparison of a diabetic and non-diabetic group within the cohort by multi-group CFA revealed that the diabetic cohort showed reduced capacities in the metabolism and salt domains and higher variabilities of the biomarkers belonging to these domains. The variability-based network analysis visualizes the concept of homeostasis and could be a valuable tool for exploring both healthy and pathological conditions.
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Affiliation(s)
- Yuichi Nakazato
- Division of Nephrology, Yuai Nisshin Clinic, Hakuyukai Medical Corporation, 2-1914-6 Nisshin-Cho, Kita-Ku, Saitama, Saitama, 331-0823, Japan.
| | - Masahiro Shimoyama
- Division of Nephrology, Yuai Clinic, Hakuyukai Medical Corporation, Saitama, Japan
| | - Alan A Cohen
- PRIMUS Research Group, Department of Family Medicine, University of Sherbrooke, Sherbrooke, QC, Canada
- Butler Columbia Aging Center, Mailman School of Public Health, Columbia University, New York, NY, USA
- Department of Environmental Health Sciences, Mailman School of Public Health, Columbia University, New York, NY, USA
| | - Akihisa Watanabe
- Division of Nephrology, Yuai Minuma Clinic, Hakuyukai Medical Corporation, Saitama, Japan
| | - Hiroaki Kobayashi
- Division of Nephrology, Yuai Mihashi Clinic, Hakuyukai Medical Corporation, Saitama, Japan
| | - Hirofumi Shimoyama
- Division of Nephrology, Yuai Nisshin Clinic, Hakuyukai Medical Corporation, 2-1914-6 Nisshin-Cho, Kita-Ku, Saitama, Saitama, 331-0823, Japan
| | - Hiromi Shimoyama
- Division of Nephrology, Yuai Clinic, Hakuyukai Medical Corporation, Saitama, Japan
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Torres-Ortega R, Guillén-Alonso H, Alcalde-Vázquez R, Ramírez-Chávez E, Molina-Torres J, Winkler R. In Vivo Low-Temperature Plasma Ionization Mass Spectrometry (LTP-MS) Reveals Regulation of 6-Pentyl-2H-Pyran-2-One (6-PP) as a Physiological Variable during Plant-Fungal Interaction. Metabolites 2022; 12:metabo12121231. [PMID: 36557269 PMCID: PMC9783819 DOI: 10.3390/metabo12121231] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/26/2022] [Revised: 11/22/2022] [Accepted: 11/29/2022] [Indexed: 12/13/2022] Open
Abstract
Volatile organic compounds (VOCs) comprises a broad class of small molecules (up to ~300 g/mol) produced by biological and non-biological sources. VOCs play a vital role in an organism's metabolism during its growth, defense, and reproduction. The well-known 6-pentyl-α-pyrone (6-PP) molecule is an example of a major volatile biosynthesized by Trichoderma atroviride that modulates the expression of PIN auxin-transport proteins in primary roots of Arabidopsis thaliana during their relationship. Their beneficial relation includes lateral root formation, defense induction, and increased plant biomass production. The role of 6-PP has been widely studied due to its relevance in this cross-kingdom relationship. Conventional VOCs measurements are often destructive; samples require further preparation, and the time resolution is low (around hours). Some techniques enable at-line or real-time analyses but are highly selective to defined compounds. Due to these technical constraints, it is difficult to acquire relevant information about the dynamics of VOCs in biological systems. Low-temperature plasma (LTP) ionization allows the analysis of a wide range of VOCs by mass spectrometry (MS). In addition, LTP-MS requires no sample preparation, is solvent-free, and enables the detection of 6-PP faster than conventional analytical methods. Applying static statistical methods such as Principal Component Analysis (PCA) and Discriminant Factorial Analysis (DFA) leads to a loss of information since the biological systems are dynamic. Thus, we applied a time series analysis to find patterns in the signal changes. Our results indicate that the 6-PP signal is constitutively emitted by T. atroviride only; the signal shows high skewness and kurtosis. In A. thaliana grown alone, no signal corresponding to 6-PP is detected above the white noise level. However, during T. atroviride-A. thaliana interaction, the signal performance showed reduced skewness and kurtosis with high autocorrelation. These results suggest that 6-PP is a physiological variable that promotes homeostasis during the plant-fungal relationship. Although the molecular mechanism of this cross-kingdom control is still unknown, our study indicates that 6-PP has to be regulated by A. thaliana during their interaction.
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Affiliation(s)
- Rosina Torres-Ortega
- Department of Biotechnology and Biochemistry, Center for Research and Advanced Studies (CINVESTAV), Irapuato 36824, Mexico
- UGA-Langebio, Center for Research and Advanced Studies (CINVESTAV) Irapuato, Km. 9.6 Libramiento Norte Carr. Irapuato-León, Irapuato 36824, Mexico
| | - Héctor Guillén-Alonso
- Department of Biotechnology and Biochemistry, Center for Research and Advanced Studies (CINVESTAV), Irapuato 36824, Mexico
- UGA-Langebio, Center for Research and Advanced Studies (CINVESTAV) Irapuato, Km. 9.6 Libramiento Norte Carr. Irapuato-León, Irapuato 36824, Mexico
- Department of Biochemical Engineering, Nacional Technological Institute, Celaya 38010, Mexico
| | - Raúl Alcalde-Vázquez
- Department of Biotechnology and Biochemistry, Center for Research and Advanced Studies (CINVESTAV), Irapuato 36824, Mexico
- UGA-Langebio, Center for Research and Advanced Studies (CINVESTAV) Irapuato, Km. 9.6 Libramiento Norte Carr. Irapuato-León, Irapuato 36824, Mexico
| | - Enrique Ramírez-Chávez
- Department of Biotechnology and Biochemistry, Center for Research and Advanced Studies (CINVESTAV), Irapuato 36824, Mexico
| | - Jorge Molina-Torres
- Department of Biotechnology and Biochemistry, Center for Research and Advanced Studies (CINVESTAV), Irapuato 36824, Mexico
| | - Robert Winkler
- Department of Biotechnology and Biochemistry, Center for Research and Advanced Studies (CINVESTAV), Irapuato 36824, Mexico
- UGA-Langebio, Center for Research and Advanced Studies (CINVESTAV) Irapuato, Km. 9.6 Libramiento Norte Carr. Irapuato-León, Irapuato 36824, Mexico
- Correspondence:
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Kraemer MB, Garbuio ALP, Kaneko LO, Gobatto CA, Manchado-Gobatto FB, dos Reis IGM, Messias LHD. Associations among sleep, hematologic profile, and aerobic and anerobic capacity of young swimmers: A complex network approach. Front Physiol 2022; 13:948422. [PMID: 36091363 PMCID: PMC9448919 DOI: 10.3389/fphys.2022.948422] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/19/2022] [Accepted: 07/07/2022] [Indexed: 11/13/2022] Open
Abstract
Although the link between sleep and hematological parameters is well-described, it is unclear how this integration affects the swimmer’s performance. The parameters derived from the non-invasive critical velocity protocol have been extensively used to evaluate these athletes, especially the aerobic capacity (critical velocity—CV) and the anaerobic work capacity (AWC). Thus, this study applied the complex network model to verify the influence of sleep and hematological variables on the CV and AWC of young swimmers. Thirty-eight swimmers (male, n = 20; female, n = 18) completed five experimental evaluations. Initially, the athletes attended the laboratory facilities for venous blood collection, anthropometric measurements, and application of sleep questionnaires. Over the 4 subsequent days, athletes performed randomized maximal efforts on distances of 100, 200, 400, and 800-m. The aerobic and anerobic parameters were determined by linear function between distance vs. time, where CV relates to the slope of regression and AWC to y-intercept. Weighted but untargeted networks were generated based on significant (p < 0.05) correlations among variables regardless of the correlation coefficient. Betweenness and eigenvector metrics were used to highlight the more important nodes inside the complex network. Regardless of the centrality metric, basophils and red blood cells appeared as influential nodes in the networks with AWC or CV as targets. The role of other hematologic components was also revealed in these metrics, along with sleep total time. Overall, these results trigger new discussion on the influence of sleep and hematologic profile on the swimmer’s performance, and the relationships presented by this targeted complex network can be an important tool throughout the athlete’s development.
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Affiliation(s)
- Mauricio Beitia Kraemer
- Research Group on Technology Applied to Exercise Physiology (GTAFE), Laboratory of Multidisciplinary Research, São Francisco University, Bragança Paulista, Brazil
| | - Ana Luíza Paula Garbuio
- Research Group on Technology Applied to Exercise Physiology (GTAFE), Laboratory of Multidisciplinary Research, São Francisco University, Bragança Paulista, Brazil
| | - Luisa Oliveira Kaneko
- Research Group on Technology Applied to Exercise Physiology (GTAFE), Laboratory of Multidisciplinary Research, São Francisco University, Bragança Paulista, Brazil
| | - Claudio Alexandre Gobatto
- Laboratory of Applied Sport Physiology, School of Applied Sciences, University of Campinas, Limeira, Brazil
| | | | - Ivan Gustavo Masseli dos Reis
- Research Group on Technology Applied to Exercise Physiology (GTAFE), Laboratory of Multidisciplinary Research, São Francisco University, Bragança Paulista, Brazil
| | - Leonardo Henrique Dalcheco Messias
- Research Group on Technology Applied to Exercise Physiology (GTAFE), Laboratory of Multidisciplinary Research, São Francisco University, Bragança Paulista, Brazil
- *Correspondence: Leonardo Henrique Dalcheco Messias,
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Barajas-Martínez A, Mehta R, Ibarra-Coronado E, Fossion R, Martínez Garcés VJ, Arellano MR, González Alvarez IA, Bautista YVM, Bello-Chavolla OY, Pedraza NR, Encinas BR, Carrión CIP, Ávila MIJ, Valladares-García JC, Vanegas-Cedillo PE, Juárez DH, Vargas-Vázquez A, Antonio-Villa NE, Almeda-Valdes P, Resendis-Antonio O, Hiriart M, Frank A, Aguilar-Salinas CA, Rivera AL. Physiological Network Is Disrupted in Severe COVID-19. Front Physiol 2022; 13:848172. [PMID: 35360235 PMCID: PMC8961032 DOI: 10.3389/fphys.2022.848172] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/04/2022] [Accepted: 02/02/2022] [Indexed: 11/13/2022] Open
Abstract
The human body is a complex system maintained in homeostasis thanks to the interactions between multiple physiological regulation systems. When faced with physical or biological perturbations, this system must react by keeping a balance between adaptability and robustness. The SARS-COV-2 virus infection poses an immune system challenge that tests the organism's homeostatic response. Notably, the elderly and men are particularly vulnerable to severe disease, poor outcomes, and death. Mexico seems to have more infected young men than anywhere else. The goal of this study is to determine the differences in the relationships that link physiological variables that characterize the elderly and men, and those that characterize fatal outcomes in young men. To accomplish this, we examined a database of patients with moderate to severe COVID-19 (471 men and 277 women) registered at the "Instituto Nacional de Ciencias Médicas y Nutrición Salvador Zubirán" in March 2020. The sample was stratified by outcome, age, and sex. Physiological networks were built using 67 physiological variables (vital signs, anthropometric, hematic, biochemical, and tomographic variables) recorded upon hospital admission. Individual variables and system behavior were examined by descriptive statistics, differences between groups, principal component analysis, and network analysis. We show how topological network properties, particularly clustering coefficient, become disrupted in disease. Finally, anthropometric, metabolic, inflammatory, and pulmonary cluster interaction characterize the deceased young male group.
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Affiliation(s)
- Antonio Barajas-Martínez
- Centro de Ciencias de la Complejidad, Universidad Nacional Autónoma de México, Ciudad de México, Mexico
- Facultad de Medicina, Universidad Nacional Autónoma de México, Ciudad de México, Mexico
- Programa de Doctorado en Ciencias Biomédicas, Universidad Nacional Autónoma de México, Ciudad de México, Mexico
| | - Roopa Mehta
- Unidad de Investigación de Enfermedades Metabólicas, Instituto Nacional de Ciencias Médicas y Nutrición “Salvador Zubirán”, Ciudad de México, Mexico
| | | | - Ruben Fossion
- Centro de Ciencias de la Complejidad, Universidad Nacional Autónoma de México, Ciudad de México, Mexico
- Instituto de Ciencias Nucleares, Universidad Nacional Autónoma de México, Ciudad de México, Mexico
| | - Vania J. Martínez Garcés
- Facultad de Medicina, Universidad Nacional Autónoma de México, Ciudad de México, Mexico
- Plan of Combined Studies in Medicine (PECEM-MD/PhD), Facultad de Medicina, Universidad Nacional Autónoma de México, Ciudad de México, Mexico
| | - Monserrat Ramírez Arellano
- Facultad de Medicina, Universidad Nacional Autónoma de México, Ciudad de México, Mexico
- Plan of Combined Studies in Medicine (PECEM-MD/PhD), Facultad de Medicina, Universidad Nacional Autónoma de México, Ciudad de México, Mexico
| | | | | | | | - Natalia Ramírez Pedraza
- Departamento de Radiología, Instituto Nacional de Ciencias Médicas y Nutrición “Salvador Zubirán”, Ciudad de México, Mexico
| | - Bethsabel Rodríguez Encinas
- Departamento de Radiología, Instituto Nacional de Ciencias Médicas y Nutrición “Salvador Zubirán”, Ciudad de México, Mexico
| | - Carolina Isabel Pérez Carrión
- Departamento de Endocrinología y Metabolismo, Instituto Nacional de Ciencias Médicas y Nutrición “Salvador Zubirán”, Ciudad de México, Mexico
| | - María Isabel Jasso Ávila
- Departamento de Endocrinología y Metabolismo, Instituto Nacional de Ciencias Médicas y Nutrición “Salvador Zubirán”, Ciudad de México, Mexico
| | - Jorge Carlos Valladares-García
- Departamento de Endocrinología y Metabolismo, Instituto Nacional de Ciencias Médicas y Nutrición “Salvador Zubirán”, Ciudad de México, Mexico
| | - Pablo Esteban Vanegas-Cedillo
- Departamento de Endocrinología y Metabolismo, Instituto Nacional de Ciencias Médicas y Nutrición “Salvador Zubirán”, Ciudad de México, Mexico
| | - Diana Hernández Juárez
- Departamento de Endocrinología y Metabolismo, Instituto Nacional de Ciencias Médicas y Nutrición “Salvador Zubirán”, Ciudad de México, Mexico
| | - Arsenio Vargas-Vázquez
- Facultad de Medicina, Universidad Nacional Autónoma de México, Ciudad de México, Mexico
- Plan of Combined Studies in Medicine (PECEM-MD/PhD), Facultad de Medicina, Universidad Nacional Autónoma de México, Ciudad de México, Mexico
| | - Neftali Eduardo Antonio-Villa
- Facultad de Medicina, Universidad Nacional Autónoma de México, Ciudad de México, Mexico
- Plan of Combined Studies in Medicine (PECEM-MD/PhD), Facultad de Medicina, Universidad Nacional Autónoma de México, Ciudad de México, Mexico
| | - Paloma Almeda-Valdes
- Unidad de Investigación de Enfermedades Metabólicas, Instituto Nacional de Ciencias Médicas y Nutrición “Salvador Zubirán”, Ciudad de México, Mexico
| | - Osbaldo Resendis-Antonio
- Centro de Ciencias de la Complejidad, Universidad Nacional Autónoma de México, Ciudad de México, Mexico
- Instituto Nacional de Medicina Genómica & Coordinación de la Investigación Científica-Red de Apoyo a la Investigación, UNAM, Ciudad de México, Mexico
| | - Marcia Hiriart
- Instituto de Fisiología Celular, Universidad Nacional Autónoma de México, Ciudad de México, Mexico
| | - Alejandro Frank
- Centro de Ciencias de la Complejidad, Universidad Nacional Autónoma de México, Ciudad de México, Mexico
- Instituto de Ciencias Nucleares, Universidad Nacional Autónoma de México, Ciudad de México, Mexico
- El Colegio Nacional, Mexico City, Mexico
| | - Carlos A. Aguilar-Salinas
- Unidad de Investigación de Enfermedades Metabólicas, Instituto Nacional de Ciencias Médicas y Nutrición “Salvador Zubirán”, Ciudad de México, Mexico
| | - Ana Leonor Rivera
- Centro de Ciencias de la Complejidad, Universidad Nacional Autónoma de México, Ciudad de México, Mexico
- Instituto de Ciencias Nucleares, Universidad Nacional Autónoma de México, Ciudad de México, Mexico
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7
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Martínez-González JU, Riascos AP. Activity of vehicles in the bus rapid transit system Metrobús in Mexico City. Sci Rep 2022; 12:98. [PMID: 34997045 PMCID: PMC8742109 DOI: 10.1038/s41598-021-04037-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/21/2021] [Accepted: 12/10/2021] [Indexed: 12/27/2022] Open
Abstract
In this paper, we analyze a massive dataset with registers of the movement of vehicles in the bus rapid transit system Metrobús in Mexico City from February 2020 to April 2021. With these records and a division of the system into 214 geographical regions (segments), we characterize the vehicles' activity through the statistical analysis of speeds in each zone. We use the Kullback-Leibler distance to compare the movement of vehicles in each segment and its evolution. The results for the dynamics in different zones are represented as a network where nodes define segments of the system Metrobús and edges describe similarity in the activity of vehicles. Community detection algorithms in this network allow the identification of patterns considering different levels of similarity in the distribution of speeds providing a framework for unsupervised classification of the movement of vehicles. The methods developed in this research are general and can be implemented to describe the activity of different transportation systems with detailed records of the movement of users or vehicles.
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Affiliation(s)
- Jaspe U Martínez-González
- Instituto de Física, Universidad Nacional Autónoma de México, Ciudad Universitaria, 04510, Mexico City, Mexico
| | - Alejandro P Riascos
- Instituto de Física, Universidad Nacional Autónoma de México, Ciudad Universitaria, 04510, Mexico City, Mexico.
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8
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Tamolienė V, Remmel L, Gruodyte-Raciene R, Jürimäe J. Relationships of Bone Mineral Variables with Body Composition, Blood Hormones and Training Volume in Adolescent Female Athletes with Different Loading Patterns. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2021; 18:ijerph18126571. [PMID: 34207239 PMCID: PMC8296434 DOI: 10.3390/ijerph18126571] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 05/27/2021] [Revised: 06/15/2021] [Accepted: 06/15/2021] [Indexed: 12/24/2022]
Abstract
The aim of this investigation was to determine the relationships of areal bone mineral density (aBMD) and content (BMC) with body composition, blood hormone and training load variables in adolescent female athletes with different loading patterns. The participants were 73 healthy adolescent females (14–18 years), who were divided into three groups: rhythmic gymnasts (RG; n = 33), swimmers (SW; n = 20) and untrained controls (UC; n = 20). Bone mineral and body compositional variables were measured by dual-energy X-ray absorptiometry, and insulin-like growth factor-1 (IGF-1), estradiol and leptin were analyzed from blood samples. In addition, aerobic performance was assessed by a peak oxygen consumption test. No differences (p > 0.05) in weekly training volume were observed between rhythmic gymnasts (17.6 ± 5.3 h/week) and swimmers (16.1 ± 6.9 h/week). Measured areal bone mineral density and bone mineral content values were higher in rhythmic gymnasts compared with other groups (p < 0.05), while no differences (p > 0.05) in measured bone mineral values were seen between swimmers and untrained control groups. Multiple regression models indicated that IGF-1 alone explained 14% of the total variance (R2 × 100) in lumbar spine aBMD, while appendicular muscle mass and training volume together explained 37% of the total variance in femoral neck BMC in the rhythmic gymnast group only. In swimmers, age at menarche, estradiol and appendicular muscle mass together explained 68% of the total variance in lumbar spine BMC, while appendicular muscle mass was the only predictor and explained 19 to 53% of the total variance in measured bone mineral values in untrained controls. In conclusion, adolescent rhythmic gymnasts with specific weight-bearing athletic activity present higher areal bone mineral values in comparison with swimmers and untrained controls. Specific training volume together with appendicular muscle mass influenced cortical bone development at the femoral neck site of the skeleton in rhythmic gymnasts, while hormonal values influenced trabecular bone development at the lumbar spine site in both athletic groups with different loading patterns.
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Affiliation(s)
- Vita Tamolienė
- Institute of Sports Science and Innovations, Lithuanian Sports University, LT-44221 Kaunas, Lithuania;
| | - Liina Remmel
- Institute of Sport Sciences and Physiotherapy, Faculty of Medicine, University of Tartu, 50090 Tartu, Estonia;
| | - Rita Gruodyte-Raciene
- Department of Physical and Social Education, Lithuanian Sports University, LT-44221 Kaunas, Lithuania;
| | - Jaak Jürimäe
- Institute of Sport Sciences and Physiotherapy, Faculty of Medicine, University of Tartu, 50090 Tartu, Estonia;
- Correspondence:
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9
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Barajas-Martínez A, Ibarra-Coronado E, Fossion R, Toledo-Roy JC, Martínez-Garcés V, López-Rivera JA, Tello-Santoyo G, Lavin RD, Gómez JL, Stephens CR, Aguilar-Salinas CA, Estañol B, Torres N, Tovar AR, Resendis-Antonio O, Hiriart M, Frank A, Rivera AL. Sex Differences in the Physiological Network of Healthy Young Subjects. Front Physiol 2021; 12:678507. [PMID: 34045977 PMCID: PMC8144508 DOI: 10.3389/fphys.2021.678507] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/09/2021] [Accepted: 04/12/2021] [Indexed: 01/21/2023] Open
Abstract
Within human physiology, systemic interactions couple physiological variables to maintain homeostasis. These interactions change according to health status and are modified by factors such as age and sex. For several physiological processes, sex-based distinctions in normal physiology are present and defined in isolation. However, new methodologies are indispensable to analyze system-wide properties and interactions with the objective of exploring differences between sexes. Here we propose a new method to construct complex inferential networks from a normalization using the clinical criteria for health of physiological variables, and the correlations between anthropometric and blood tests biomarkers of 198 healthy young participants (117 women, 81 men, from 18 to 27 years old). Physiological networks of men have less correlations, displayed higher modularity, higher small-world index, but were more vulnerable to directed attacks, whereas networks of women were more resilient. The networks of both men and women displayed sex-specific connections that are consistent with the literature. Additionally, we carried out a time-series study on heart rate variability (HRV) using Physionet's Fantasia database. Autocorrelation of HRV, variance, and Poincare's plots, as a measure of variability, are statistically significant higher in young men and statistically significant different from young women. These differences are attenuated in older men and women, that have similar HRV distributions. The network approach revealed differences in the association of variables related to glucose homeostasis, nitrogen balance, kidney function, and fat depots. The clusters of physiological variables and their roles within the network remained similar regardless of sex. Both methodologies show a higher number of associations between variables in the physiological system of women, implying redundant mechanisms of control and simultaneously showing that these systems display less variability in time than those of men, constituting a more resilient system.
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Affiliation(s)
- Antonio Barajas-Martínez
- Doctorado en Ciencias Biomédicas, Universidad Nacional Autónoma de México, Mexico City, Mexico.,Centro de Ciencias de la Complejidad, Universidad Nacional Autónoma de México, Mexico City, Mexico.,Facultad de Medicina, Universidad Nacional Autónoma de México, Mexico City, Mexico
| | - Elizabeth Ibarra-Coronado
- Centro de Ciencias de la Complejidad, Universidad Nacional Autónoma de México, Mexico City, Mexico.,Instituto de Ciencias Nucleares, Universidad Nacional Autónoma de México, Mexico City, Mexico
| | - Ruben Fossion
- Centro de Ciencias de la Complejidad, Universidad Nacional Autónoma de México, Mexico City, Mexico.,Instituto de Ciencias Nucleares, Universidad Nacional Autónoma de México, Mexico City, Mexico
| | - Juan Claudio Toledo-Roy
- Centro de Ciencias de la Complejidad, Universidad Nacional Autónoma de México, Mexico City, Mexico.,Instituto de Ciencias Nucleares, Universidad Nacional Autónoma de México, Mexico City, Mexico
| | - Vania Martínez-Garcés
- Plan de Estudios Combinados en Medicina (PECEM-MD/PhD), Facultad de Medicina, Universidad Nacional Autónoma de México, Mexico City, Mexico
| | - Juan Antonio López-Rivera
- Centro de Ciencias de la Complejidad, Universidad Nacional Autónoma de México, Mexico City, Mexico.,Facultad de Ciencias, Universidad Nacional Autónoma de México, Mexico City, Mexico
| | | | - Rusland D Lavin
- Centro de Ciencias de la Complejidad, Universidad Nacional Autónoma de México, Mexico City, Mexico
| | - José Luis Gómez
- Facultad de Ciencias, Universidad Nacional Autónoma de México, Mexico City, Mexico
| | - Christopher R Stephens
- Centro de Ciencias de la Complejidad, Universidad Nacional Autónoma de México, Mexico City, Mexico.,Instituto de Ciencias Nucleares, Universidad Nacional Autónoma de México, Mexico City, Mexico
| | | | - Bruno Estañol
- Centro de Ciencias de la Complejidad, Universidad Nacional Autónoma de México, Mexico City, Mexico.,Instituto Nacional de Ciencias Médicas y Nutrición "Salvador Zubirán", Mexico City, Mexico
| | - Nimbe Torres
- Instituto Nacional de Ciencias Médicas y Nutrición "Salvador Zubirán", Mexico City, Mexico
| | - Armando R Tovar
- Instituto Nacional de Ciencias Médicas y Nutrición "Salvador Zubirán", Mexico City, Mexico
| | - Osbaldo Resendis-Antonio
- Centro de Ciencias de la Complejidad, Universidad Nacional Autónoma de México, Mexico City, Mexico.,Instituto Nacional de Medicina Genómica, Coordinación de la Investigación Científica-Red de Apoyo a la Investigación, UNAM, Mexico City, Mexico
| | - Marcia Hiriart
- Centro de Ciencias de la Complejidad, Universidad Nacional Autónoma de México, Mexico City, Mexico.,Instituto de Fisiología Celular, Mexico City, Mexico
| | - Alejandro Frank
- Centro de Ciencias de la Complejidad, Universidad Nacional Autónoma de México, Mexico City, Mexico.,Instituto de Ciencias Nucleares, Universidad Nacional Autónoma de México, Mexico City, Mexico.,El Colegio Nacional, Mexico City, Mexico
| | - Ana Leonor Rivera
- Centro de Ciencias de la Complejidad, Universidad Nacional Autónoma de México, Mexico City, Mexico.,Instituto de Ciencias Nucleares, Universidad Nacional Autónoma de México, Mexico City, Mexico
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10
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Zmazek J, Klemen MS, Markovič R, Dolenšek J, Marhl M, Stožer A, Gosak M. Assessing Different Temporal Scales of Calcium Dynamics in Networks of Beta Cell Populations. Front Physiol 2021; 12:612233. [PMID: 33833686 PMCID: PMC8021717 DOI: 10.3389/fphys.2021.612233] [Citation(s) in RCA: 22] [Impact Index Per Article: 7.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/30/2020] [Accepted: 02/26/2021] [Indexed: 01/06/2023] Open
Abstract
Beta cells within the pancreatic islets of Langerhans respond to stimulation with coherent oscillations of membrane potential and intracellular calcium concentration that presumably drive the pulsatile exocytosis of insulin. Their rhythmic activity is multimodal, resulting from networked feedback interactions of various oscillatory subsystems, such as the glycolytic, mitochondrial, and electrical/calcium components. How these oscillatory modules interact and affect the collective cellular activity, which is a prerequisite for proper hormone release, is incompletely understood. In the present work, we combined advanced confocal Ca2+ imaging in fresh mouse pancreas tissue slices with time series analysis and network science approaches to unveil the glucose-dependent characteristics of different oscillatory components on both the intra- and inter-cellular level. Our results reveal an interrelationship between the metabolically driven low-frequency component and the electrically driven high-frequency component, with the latter exhibiting the highest bursting rates around the peaks of the slow component and the lowest around the nadirs. Moreover, the activity, as well as the average synchronicity of the fast component, considerably increased with increasing stimulatory glucose concentration, whereas the stimulation level did not affect any of these parameters in the slow component domain. Remarkably, in both dynamical components, the average correlation decreased similarly with intercellular distance, which implies that intercellular communication affects the synchronicity of both types of oscillations. To explore the intra-islet synchronization patterns in more detail, we constructed functional connectivity maps. The subsequent comparison of network characteristics of different oscillatory components showed more locally clustered and segregated networks of fast oscillatory activity, while the slow oscillations were more global, resulting in several long-range connections and a more cohesive structure. Besides the structural differences, we found a relatively weak relationship between the fast and slow network layer, which suggests that different synchronization mechanisms shape the collective cellular activity in islets, a finding which has to be kept in mind in future studies employing different oscillations for constructing networks.
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Affiliation(s)
- Jan Zmazek
- Faculty of Natural Sciences and Mathematics, University of Maribor, Maribor, Slovenia
| | | | - Rene Markovič
- Faculty of Natural Sciences and Mathematics, University of Maribor, Maribor, Slovenia
- Faculty of Electrical Engineering and Computer Science, University of Maribor, Maribor, Slovenia
| | - Jurij Dolenšek
- Faculty of Natural Sciences and Mathematics, University of Maribor, Maribor, Slovenia
- Faculty of Medicine, University of Maribor, Maribor, Slovenia
| | - Marko Marhl
- Faculty of Natural Sciences and Mathematics, University of Maribor, Maribor, Slovenia
- Faculty of Medicine, University of Maribor, Maribor, Slovenia
- Faculty of Education, University of Maribor, Maribor, Slovenia
| | - Andraž Stožer
- Faculty of Medicine, University of Maribor, Maribor, Slovenia
| | - Marko Gosak
- Faculty of Natural Sciences and Mathematics, University of Maribor, Maribor, Slovenia
- Faculty of Medicine, University of Maribor, Maribor, Slovenia
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11
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Pignatelli P, Iezzi L, Pennese M, Raimondi P, Cichella A, Bondi D, Grande R, Cotellese R, Di Bartolomeo N, Innocenti P, Piattelli A, Curia MC. The Potential of Colonic Tumor Tissue Fusobacterium nucleatum to Predict Staging and Its Interplay with Oral Abundance in Colon Cancer Patients. Cancers (Basel) 2021; 13:1032. [PMID: 33804585 PMCID: PMC7957509 DOI: 10.3390/cancers13051032] [Citation(s) in RCA: 20] [Impact Index Per Article: 6.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/28/2021] [Revised: 02/16/2021] [Accepted: 02/23/2021] [Indexed: 12/12/2022] Open
Abstract
BACKGROUND Intestinal microbiota dysbiosis may enhance the carcinogenicity of colon cancer (CC) by the proliferation and differentiation of epithelial cells. Oral Fusobacterium nucleatum (Fn) and Porphyromonas gingivalis (Pg) have the ability to invade the gut epithelium, promoting tumor progression. The aim of the study was to assess whether the abundance of these odontopathogenic bacteria was associated with colon cancer. We also investigated how lifestyle factors could influence the oral Fn and Pg abundance and CC. METHODS Thirty-six CC patients were included in the study to assess the Pg and Fn oral and colon tissue abundance by qPCR. Oral health data, food habits and lifestyles were also recorded. RESULTS Patients had a greater quantity of Fn in the oral cavity than matched CC and adjacent non-neoplastic mucosa (adj t) tissues (p = 0.004 and p < 0.001). Instead, Pg was not significantly detected in colonic tissues. There was an association between the Fn quantity in the oral and CC tissue and a statistically significant relation between the Fn abundance in adenocarcinoma (ADK) and staging (p = 0.016). The statistical analysis revealed a tendency towards a greater Fn quantity in CC (p = 0.073, η2p = 0.12) for high-meat consumers. CONCLUSION In our study, Pg was absent in colon tissues but was correlated with the oral inflammation gingival and plaque indices. For the first time, there was evidence that the Fn oral concentration can influence colon tissue concentrations and predict CC prognosis.
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Affiliation(s)
- Pamela Pignatelli
- Department of Medical, Oral and Biotechnological Sciences, “G. d’Annunzio” University of Chieti-Pescara, Via dei Vestini, 66100 Chieti, Italy; (P.P.); (L.I.); (M.P.); (R.C.); (A.P.)
| | - Lorena Iezzi
- Department of Medical, Oral and Biotechnological Sciences, “G. d’Annunzio” University of Chieti-Pescara, Via dei Vestini, 66100 Chieti, Italy; (P.P.); (L.I.); (M.P.); (R.C.); (A.P.)
| | - Martina Pennese
- Department of Medical, Oral and Biotechnological Sciences, “G. d’Annunzio” University of Chieti-Pescara, Via dei Vestini, 66100 Chieti, Italy; (P.P.); (L.I.); (M.P.); (R.C.); (A.P.)
| | - Paolo Raimondi
- Department of General Surgery, Private Hospital “Villa Serena”, Città Sant’Angelo, 65013 Pescara, Italy; (P.R.); (A.C.); (N.D.B.); (P.I.)
| | - Anna Cichella
- Department of General Surgery, Private Hospital “Villa Serena”, Città Sant’Angelo, 65013 Pescara, Italy; (P.R.); (A.C.); (N.D.B.); (P.I.)
| | - Danilo Bondi
- Department of Neuroscience, Imaging and Clinical Sciences, “G. d’Annunzio” University of Chieti-Pescara, Via dei Vestini, 66100 Chieti, Italy;
| | - Rossella Grande
- Department of Pharmacy, “G. d’Annunzio” University of Chieti-Pescara, Via dei Vestini, 66100 Chieti, Italy;
| | - Roberto Cotellese
- Department of Medical, Oral and Biotechnological Sciences, “G. d’Annunzio” University of Chieti-Pescara, Via dei Vestini, 66100 Chieti, Italy; (P.P.); (L.I.); (M.P.); (R.C.); (A.P.)
- Villa Serena Foundation for Research, Città Sant’Angelo, 65013 Pescara, Italy
| | - Nicola Di Bartolomeo
- Department of General Surgery, Private Hospital “Villa Serena”, Città Sant’Angelo, 65013 Pescara, Italy; (P.R.); (A.C.); (N.D.B.); (P.I.)
| | - Paolo Innocenti
- Department of General Surgery, Private Hospital “Villa Serena”, Città Sant’Angelo, 65013 Pescara, Italy; (P.R.); (A.C.); (N.D.B.); (P.I.)
- Villa Serena Foundation for Research, Città Sant’Angelo, 65013 Pescara, Italy
| | - Adriano Piattelli
- Department of Medical, Oral and Biotechnological Sciences, “G. d’Annunzio” University of Chieti-Pescara, Via dei Vestini, 66100 Chieti, Italy; (P.P.); (L.I.); (M.P.); (R.C.); (A.P.)
- Villa Serena Foundation for Research, Città Sant’Angelo, 65013 Pescara, Italy
| | - Maria Cristina Curia
- Department of Medical, Oral and Biotechnological Sciences, “G. d’Annunzio” University of Chieti-Pescara, Via dei Vestini, 66100 Chieti, Italy; (P.P.); (L.I.); (M.P.); (R.C.); (A.P.)
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12
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Cohen AA, Leblanc S, Roucou X. Robust Physiological Metrics From Sparsely Sampled Networks. Front Physiol 2021; 12:624097. [PMID: 33643068 PMCID: PMC7902772 DOI: 10.3389/fphys.2021.624097] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/30/2020] [Accepted: 01/12/2021] [Indexed: 12/14/2022] Open
Abstract
Physiological and biochemical networks are highly complex, involving thousands of nodes as well as a hierarchical structure. True network structure is also rarely known. This presents major challenges for applying classical network theory to these networks. However, complex systems generally share the property of having a diffuse or distributed signal. Accordingly, we should predict that system state can be robustly estimated with sparse sampling, and with limited knowledge of true network structure. In this review, we summarize recent findings from several methodologies to estimate system state via a limited sample of biomarkers, notably Mahalanobis distance, principal components analysis, and cluster analysis. While statistically simple, these methods allow novel characterizations of system state when applied judiciously. Broadly, system state can often be estimated even from random samples of biomarkers. Furthermore, appropriate methods can detect emergent underlying physiological structure from this sparse data. We propose that approaches such as these are a powerful tool to understand physiology, and could lead to a new understanding and mapping of the functional implications of biological variation.
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Affiliation(s)
- Alan A. Cohen
- Groupe de Recherche PRIMUS, Département de Médecine de Famille et de Médecine d’Urgence, Université de Sherbrooke, Sherbrooke, QC, Canada
- Centre de Recherche, Centre Hospitalier Universitaire de Sherbrooke (CRCHUS), Sherbrooke, QC, Canada
- Research Center on Aging, CIUSSS-de-l’Estrie-CHUS, Sherbrooke, QC, Canada
| | - Sebastien Leblanc
- Département de Biochimie et de Génomique Fonctionnelle, Université de Sherbrooke, Sherbrooke, QC, Canada
| | - Xavier Roucou
- Département de Biochimie et de Génomique Fonctionnelle, Université de Sherbrooke, Sherbrooke, QC, Canada
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13
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Barajas-Martínez A, Ibarra-Coronado E, Sierra-Vargas MP, Cruz-Bautista I, Almeda-Valdes P, Aguilar-Salinas CA, Fossion R, Stephens CR, Vargas-Domínguez C, Atzatzi-Aguilar OG, Debray-García Y, García-Torrentera R, Bobadilla K, Naranjo Meneses MA, Mena Orozco DA, Lam-Chung CE, Martínez Garcés V, Lecona OA, Marín-García AO, Frank A, Rivera AL. Physiological Network From Anthropometric and Blood Test Biomarkers. Front Physiol 2021; 11:612598. [PMID: 33510648 PMCID: PMC7835885 DOI: 10.3389/fphys.2020.612598] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/30/2020] [Accepted: 12/16/2020] [Indexed: 12/12/2022] Open
Abstract
Currently, research in physiology focuses on molecular mechanisms underlying the functioning of living organisms. Reductionist strategies are used to decompose systems into their components and to measure changes of physiological variables between experimental conditions. However, how these isolated physiological variables translate into the emergence -and collapse- of biological functions of the organism as a whole is often a less tractable question. To generate a useful representation of physiology as a system, known and unknown interactions between heterogeneous physiological components must be taken into account. In this work we use a Complex Inference Networks approach to build physiological networks from biomarkers. We employ two unrelated databases to generate Spearman correlation matrices of 81 and 54 physiological variables, respectively, including endocrine, mechanic, biochemical, anthropometric, physiological, and cellular variables. From these correlation matrices we generated physiological networks by selecting a p-value threshold indicating statistically significant links. We compared the networks from both samples to show which features are robust and representative for physiology in health. We found that although network topology is sensitive to the p-value threshold, an optimal value may be defined by combining criteria of stability of topological features and network connectedness. Unsupervised community detection algorithms allowed to obtain functional clusters that correlate well with current medical knowledge. Finally, we describe the topology of the physiological networks, which lie between random and ordered structural features, and may reflect system robustness and adaptability. Modularity of physiological networks allows to explore functional clusters that are consistent even when considering different physiological variables. Altogether Complex Inference Networks from biomarkers provide an efficient implementation of a systems biology approach that is visually understandable and robust. We hypothesize that physiological networks allow to translate concepts such as homeostasis into quantifiable properties of biological systems useful for determination and quantification of health and disease.
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Affiliation(s)
- Antonio Barajas-Martínez
- Posgrado en Ciencias Biomédicas, Facultad de Medicina, Universidad Nacional Autónoma de México, Ciudad de México, Mexico.,Centro de Ciencias de la Complejidad, Universidad Nacional Autónoma de México, Ciudad de México, Mexico
| | - Elizabeth Ibarra-Coronado
- Centro de Ciencias de la Complejidad, Universidad Nacional Autónoma de México, Ciudad de México, Mexico.,Instituto de Ciencias Nucleares, Universidad Nacional Autónoma de México, Ciudad de México, Mexico
| | - Martha Patricia Sierra-Vargas
- Subdirección de Investigación Clínica, Instituto Nacional de Enfermedades Respiratorias, Ciudad de México, Mexico.,Facultad Mexicana de Medicina, Universidad La Salle, Ciudad de México, Mexico
| | - Ivette Cruz-Bautista
- Unidad de Investigación en Enfermedades Metabólicas, Instituto Nacional de Ciencias Médicas y Nutrición Salvador Zubirán, Ciudad de México, Mexico
| | - Paloma Almeda-Valdes
- Unidad de Investigación en Enfermedades Metabólicas, Instituto Nacional de Ciencias Médicas y Nutrición Salvador Zubirán, Ciudad de México, Mexico
| | - Carlos A Aguilar-Salinas
- Centro de Ciencias de la Complejidad, Universidad Nacional Autónoma de México, Ciudad de México, Mexico.,Unidad de Investigación en Enfermedades Metabólicas, Instituto Nacional de Ciencias Médicas y Nutrición Salvador Zubirán, Ciudad de México, Mexico.,Tecnológico de Monterrey, Escuela de Medicina y Ciencias de la Salud, Monterrey, Mexico
| | - Ruben Fossion
- Centro de Ciencias de la Complejidad, Universidad Nacional Autónoma de México, Ciudad de México, Mexico.,Instituto de Ciencias Nucleares, Universidad Nacional Autónoma de México, Ciudad de México, Mexico
| | - Christopher R Stephens
- Centro de Ciencias de la Complejidad, Universidad Nacional Autónoma de México, Ciudad de México, Mexico.,Instituto de Ciencias Nucleares, Universidad Nacional Autónoma de México, Ciudad de México, Mexico
| | - Claudia Vargas-Domínguez
- Departamento de Investigación en Inmunología y Medicina Ambiental, Instituto Nacional de Enfermedades Respiratorias, Ciudad de México, Mexico
| | - Octavio Gamaliel Atzatzi-Aguilar
- Departamento de Investigación en Inmunología y Medicina Ambiental, Instituto Nacional de Enfermedades Respiratorias, Ciudad de México, Mexico.,Cátedras CONACYT, Ciudad de México, Mexico
| | - Yazmín Debray-García
- Departamento de Investigación en Inmunología y Medicina Ambiental, Instituto Nacional de Enfermedades Respiratorias, Ciudad de México, Mexico
| | - Rogelio García-Torrentera
- Unidad de Urgencias Respiratorias, Instituto Nacional de Enfermedades Respiratorias, Ciudad de México, Mexico
| | - Karen Bobadilla
- Departamento de Investigación en Inmunología y Medicina Ambiental, Instituto Nacional de Enfermedades Respiratorias, Ciudad de México, Mexico
| | - María Augusta Naranjo Meneses
- Unidad de Investigación en Enfermedades Metabólicas, Instituto Nacional de Ciencias Médicas y Nutrición Salvador Zubirán, Ciudad de México, Mexico
| | - Dulce Abril Mena Orozco
- Unidad de Investigación en Enfermedades Metabólicas, Instituto Nacional de Ciencias Médicas y Nutrición Salvador Zubirán, Ciudad de México, Mexico
| | - César Ernesto Lam-Chung
- Unidad de Investigación en Enfermedades Metabólicas, Instituto Nacional de Ciencias Médicas y Nutrición Salvador Zubirán, Ciudad de México, Mexico
| | - Vania Martínez Garcés
- Programa de Estudios Combinados en Medicina, Facultad de Medicina, Universidad Nacional Autónoma de México, Ciudad de México, Mexico
| | - Octavio A Lecona
- Posgrado en Ciencias Biomédicas, Facultad de Medicina, Universidad Nacional Autónoma de México, Ciudad de México, Mexico.,Centro de Ciencias de la Complejidad, Universidad Nacional Autónoma de México, Ciudad de México, Mexico
| | - Arlex O Marín-García
- Centro de Ciencias de la Complejidad, Universidad Nacional Autónoma de México, Ciudad de México, Mexico
| | - Alejandro Frank
- Centro de Ciencias de la Complejidad, Universidad Nacional Autónoma de México, Ciudad de México, Mexico.,Instituto de Ciencias Nucleares, Universidad Nacional Autónoma de México, Ciudad de México, Mexico.,El Colegio Nacional, Ciudad de México, Mexico
| | - Ana Leonor Rivera
- Centro de Ciencias de la Complejidad, Universidad Nacional Autónoma de México, Ciudad de México, Mexico.,Instituto de Ciencias Nucleares, Universidad Nacional Autónoma de México, Ciudad de México, Mexico
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14
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Ivanov PC. The New Field of Network Physiology: Building the Human Physiolome. FRONTIERS IN NETWORK PHYSIOLOGY 2021; 1:711778. [PMID: 36925582 PMCID: PMC10013018 DOI: 10.3389/fnetp.2021.711778] [Citation(s) in RCA: 57] [Impact Index Per Article: 19.0] [Reference Citation Analysis] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/19/2021] [Accepted: 05/21/2021] [Indexed: 12/22/2022]
Affiliation(s)
- Plamen Ch Ivanov
- Keck Laboratory for Network Physiology, Department of Physics, Boston University, Boston, MA, United States.,Harvard Medical School and Division of Sleep Medicine, Brigham and Women's Hospital, Boston, MA, United States.,Bulgarian Academy of Sciences, Institute of Solid State Physics, Sofia, Bulgaria
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