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Alonso-Forn D, Sancho-Knapik D, Fariñas MD, Nadal M, Martín-Sánchez R, Ferrio JP, de Dios VR, Peguero-Pina JJ, Onoda Y, Cavender-Bares J, Arenas TGÁ, Gil-Pelegrín E. Disentangling leaf structural and material properties in relationship to their anatomical and chemical compositional traits in oaks (Quercus L.). Ann Bot 2023; 131:789-800. [PMID: 36794926 PMCID: PMC10184456 DOI: 10.1093/aob/mcad030] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/02/2022] [Accepted: 02/15/2023] [Indexed: 05/16/2023]
Abstract
BACKGROUND AND AIMS The existence of sclerophyllous plants has been considered an adaptive strategy against different environmental stresses. Given that it literally means 'hard-leaved', it is essential to quantify the leaf mechanical properties to understand sclerophylly. However, the relative importance of each leaf trait for mechanical properties is not yet well established. METHODS Genus Quercus is an excellent system to shed light on this because it minimizes phylogenetic variation while having a wide variation in sclerophylly. We measured leaf anatomical traits and cell wall composition, analysing their relationship with leaf mass per area and leaf mechanical properties in a set of 25 oak species. KEY RESULTS The upper epidermis outer wall makes a strong and direct contribution to the leaf mechanical strength. Moreover, cellulose plays a crucial role in increasing leaf strength and toughness. The principal component analysis plot based on leaf trait values clearly separates Quercus species into two groups corresponding to evergreen and deciduous species. CONCLUSIONS Sclerophyllous Quercus species are tougher and stronger owing to their thicker epidermis outer wall and/or higher cellulose concentration. Furthermore, section Ilex species share common traits, although they occupy different climates. In addition, evergreen species living in mediterranean-type climates share common leaf traits irrespective of their different phylogenetic origin.
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Affiliation(s)
- David Alonso-Forn
- Department of Agricultural and Forest Systems and the Environment, Agrifood Research and Technology Centre of Aragon (CITA), Avda. Montañana 930, 50059 Zaragoza, Spain
| | - Domingo Sancho-Knapik
- Department of Agricultural and Forest Systems and the Environment, Agrifood Research and Technology Centre of Aragon (CITA), Avda. Montañana 930, 50059 Zaragoza, Spain
- Instituto Agroalimentario de Aragón – IA2 (CITA-Universidad de Zaragoza), Zaragoza, Spain
| | - María Dolores Fariñas
- Sensors and Ultrasonic Technologies Department, Information and Physics Technologies Institute, Spanish National Research Council (CSIC), Madrid, Spain
| | - Miquel Nadal
- Department of Agricultural and Forest Systems and the Environment, Agrifood Research and Technology Centre of Aragon (CITA), Avda. Montañana 930, 50059 Zaragoza, Spain
| | - Rubén Martín-Sánchez
- Department of Agricultural and Forest Systems and the Environment, Agrifood Research and Technology Centre of Aragon (CITA), Avda. Montañana 930, 50059 Zaragoza, Spain
| | - Juan Pedro Ferrio
- Department of Agricultural and Forest Systems and the Environment, Agrifood Research and Technology Centre of Aragon (CITA), Avda. Montañana 930, 50059 Zaragoza, Spain
- Aragon Agency for Research and Development (ARAID), E-50018 Zaragoza, Spain
| | - Víctor Resco de Dios
- School of Life Science and Engineering, Southwest University of Science and Technology, Mianyang, China
- Department of Crop and Forest Sciences, Universitat de Lleida, E-25198 Lleida, Spain
- JRU CTFC-Agrotecnio-CERCA Center, E-25198 Lleida, Spain
| | - José Javier Peguero-Pina
- Department of Agricultural and Forest Systems and the Environment, Agrifood Research and Technology Centre of Aragon (CITA), Avda. Montañana 930, 50059 Zaragoza, Spain
- Instituto Agroalimentario de Aragón – IA2 (CITA-Universidad de Zaragoza), Zaragoza, Spain
| | - Yusuke Onoda
- Division of Forest and Biomaterials Science, Graduate School of Agriculture, Kyoto University, Oiwake, Kitashirakawa, Kyoto 606-8502, Japan
| | | | - Tomás Gómez Álvarez Arenas
- Sensors and Ultrasonic Technologies Department, Information and Physics Technologies Institute, Spanish National Research Council (CSIC), Madrid, Spain
| | - Eustaquio Gil-Pelegrín
- Department of Agricultural and Forest Systems and the Environment, Agrifood Research and Technology Centre of Aragon (CITA), Avda. Montañana 930, 50059 Zaragoza, Spain
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Mérida-López S, Quintana-Orts C, Rey L, Extremera N. Teachers’ Subjective Happiness: Testing the Importance of Emotional Intelligence Facets Beyond Perceived Stress. Psychol Res Behav Manag 2022; 15:317-326. [PMID: 35210880 PMCID: PMC8859289 DOI: 10.2147/prbm.s350191] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/19/2021] [Accepted: 02/02/2022] [Indexed: 11/30/2022] Open
Abstract
Purpose Emotional intelligence (EI) is typically linked to higher subjective happiness scores in human service professionals. It is unknown which EI facets are more predictive in explaining subjective happiness beyond that accounted for by other key predictors such as perceived stress. This study investigated which EI facets were the most predictive in explaining subjective happiness above perceived stress in a relatively large sample of Spanish teachers. Methods The sample was composed of 1323 Spanish teaching professionals (821 females and 529 secondary school teachers) from different educational centers located in Southern Spain. A student-recruited sampling technique was used, and the surveys included the Wong and Law Emotional Intelligence Scale, the Subjective Happiness Scale, and the Perceived Stress Scale. Predictive and incremental validity was assessed with SPSS, and hierarchical regression analysis was used to predict subjective happiness from EI facets beyond that accounted for by perceived stress. Results The results showed that all four EI facets correlated significantly with each other. Also, they all were positively and significantly associated with subjective happiness, whereas perceived stress was negatively associated with happiness scores. Moreover, self-emotion appraisal, use of emotions and regulation of emotions accounted for a significant amount of variance in the prediction of satisfaction with life beyond the effects of sociodemographic variables and perceived stress. Conclusion This study extends the specific contribution of EI facets in predicting subjective happiness, rather than EI as a unified construct, in a relatively large sample of Spanish teachers. Self-focused dimensions involving appraisal, use and regulation of emotions appeared to be the most important predictors of happiness beyond stress experienced by teachers. Improved knowledge of the link between specific dimensions of EI and global subjective happiness might improve training in a well-being prevention program for professional development.
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Affiliation(s)
- Sergio Mérida-López
- Department of Social Psychology, Social Work, Social Anthropology and East Asian Studies at the University of Malaga, Málaga, Spain
- Correspondence: Sergio Mérida-López, Department of Social Psychology, Social Work, Social Anthropology and East Asian Studies at the University of Malaga, Málaga, Spain, Tel +34 952137570, Email
| | - Cirenia Quintana-Orts
- Department of Developmental and Educational Psychology at the University of Seville, Seville, Spain
| | - Lourdes Rey
- Department of Personality, Evaluation and Psychological Treatment at the University of Malaga, Málaga, Spain
| | - Natalio Extremera
- Department of Social Psychology, Social Work, Social Anthropology and East Asian Studies at the University of Malaga, Málaga, Spain
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Bulló M, Papandreou C, Ruiz-Canela M, Guasch-Ferré M, Li J, Hernández-Alonso P, Toledo E, Liang L, Razquin C, Corella D, Estruch R, Ros E, Fitó M, Arós F, Fiol M, Serra-Majem L, Clish CB, Becerra-Tomás N, Martínez-González MA, Hu FB, Salas-Salvadó J. Plasma Metabolomic Profiles of Glycemic Index, Glycemic Load, and Carbohydrate Quality Index in the PREDIMED Study. J Nutr 2021; 151:50-58. [PMID: 33296468 PMCID: PMC7779218 DOI: 10.1093/jn/nxaa345] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/28/2020] [Revised: 09/10/2020] [Accepted: 10/07/2020] [Indexed: 12/18/2022] Open
Abstract
BACKGROUND The quality of carbohydrate consumed, assessed by the glycemic index (GI), glycemic load (GL), or carbohydrate quality index (CQI), affects the postprandial glycemic and insulinemic responses, which have been implicated in the etiology of several chronic diseases. However, it is unclear whether plasma metabolites involved in different biological pathways could provide functional insights into the role of carbohydrate quality indices in health. OBJECTIVES We aimed to identify plasma metabolomic profiles associated with dietary GI, GL, and CQI. METHODS The present study is a cross-sectional analysis of 1833 participants with overweight/obesity (mean age = 67 y) from 2 case-cohort studies nested within the PREDIMED (Prevención con Dieta Mediterránea) trial. Data extracted from validated FFQs were used to estimate the GI, GL, and CQI. Plasma concentrations of 385 metabolites were profiled with LC coupled to MS and associations of these metabolites with those indices were assessed with elastic net regression analyses. RESULTS A total of 58, 18, and 57 metabolites were selected for GI, GL, and CQI, respectively. Choline, cotinine, γ-butyrobetaine, and 36:3 phosphatidylserine plasmalogen were positively associated with GI and GL, whereas they were negatively associated with CQI. Fructose-glucose-galactose was negatively and positively associated with GI/GL and CQI, respectively. Consistent associations of 21 metabolites with both GI and CQI were found but in opposite directions. Negative associations of kynurenic acid, 22:1 sphingomyelin, and 38:6 phosphatidylethanolamine, as well as positive associations of 32:1 phosphatidylcholine with GI and GL were also observed. Pearson correlation coefficients between GI, GL, and CQI and the metabolomic profiles were 0.30, 0.22, and 0.27, respectively. CONCLUSIONS The GI, GL, and CQI were associated with specific metabolomic profiles in a Mediterranean population at high cardiovascular disease risk. Our findings may help in understanding the role of dietary carbohydrate indices in the development of cardiometabolic disorders. This trial was registered at isrctn.com as ISRCTN35739639.
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Affiliation(s)
- Mònica Bulló
- Universitat Rovira i Virgili, Biochemistry and Biotechnology Department, Human Nutrition Unit, Reus, Spain
- Pere i Virgili Health Research Institute (IISPV), Reus, Spain
- CIBER Physiopathology of Obesity and Nutrition (CIBERobn), Institute of Health Carlos III, Madrid, Spain
- Nutrition Unit, University Hospital of Sant Joan de Reus, Reus, Spain
| | - Christopher Papandreou
- Universitat Rovira i Virgili, Biochemistry and Biotechnology Department, Human Nutrition Unit, Reus, Spain
- Pere i Virgili Health Research Institute (IISPV), Reus, Spain
- CIBER Physiopathology of Obesity and Nutrition (CIBERobn), Institute of Health Carlos III, Madrid, Spain
- Nutrition Unit, University Hospital of Sant Joan de Reus, Reus, Spain
| | - Miguel Ruiz-Canela
- CIBER Physiopathology of Obesity and Nutrition (CIBERobn), Institute of Health Carlos III, Madrid, Spain
- Department of Preventive Medicine and Public Health, University of Navarra, Pamplona, Spain
- Navarra Institute for Health Research (IdiSNA), Pamplona, Navarra, Spain
| | - Marta Guasch-Ferré
- Department of Nutrition, Harvard TH Chan School of Public Health, Boston, MA, USA
| | - Jun Li
- Department of Nutrition, Harvard TH Chan School of Public Health, Boston, MA, USA
- Department of Epidemiology, Harvard TH Chan School of Public Health, Boston, MA, USA
| | - Pablo Hernández-Alonso
- Universitat Rovira i Virgili, Biochemistry and Biotechnology Department, Human Nutrition Unit, Reus, Spain
- Pere i Virgili Health Research Institute (IISPV), Reus, Spain
- CIBER Physiopathology of Obesity and Nutrition (CIBERobn), Institute of Health Carlos III, Madrid, Spain
- Nutrition Unit, University Hospital of Sant Joan de Reus, Reus, Spain
- Department of Endocrinology and Nutrition, Virgen de la Victoria University Hospital, University of Malaga (IBIMA), Malaga, Spain
| | - Estefania Toledo
- CIBER Physiopathology of Obesity and Nutrition (CIBERobn), Institute of Health Carlos III, Madrid, Spain
- Department of Preventive Medicine and Public Health, University of Navarra, Pamplona, Spain
- Navarra Institute for Health Research (IdiSNA), Pamplona, Navarra, Spain
| | - Liming Liang
- Department of Epidemiology, Harvard TH Chan School of Public Health, Boston, MA, USA
- Department of Statistics, Harvard TH Chan School of Public Health, Boston, MA, USA
| | - Cristina Razquin
- CIBER Physiopathology of Obesity and Nutrition (CIBERobn), Institute of Health Carlos III, Madrid, Spain
- Department of Preventive Medicine and Public Health, University of Navarra, Pamplona, Spain
- Navarra Institute for Health Research (IdiSNA), Pamplona, Navarra, Spain
| | - Dolores Corella
- CIBER Physiopathology of Obesity and Nutrition (CIBERobn), Institute of Health Carlos III, Madrid, Spain
- Department of Preventive Medicine, University of Valencia, Valencia, Spain
| | - Ramon Estruch
- CIBER Physiopathology of Obesity and Nutrition (CIBERobn), Institute of Health Carlos III, Madrid, Spain
- Department of Internal Medicine, Hospital Clínic, University of Barcelona, Barcelona, Spain
- August Pi i Sunyer Biomedical Research Institute (IDIBAPS), Hospital Clinic, University of Barcelona, Barcelona, Spain
| | - Emilio Ros
- CIBER Physiopathology of Obesity and Nutrition (CIBERobn), Institute of Health Carlos III, Madrid, Spain
- August Pi i Sunyer Biomedical Research Institute (IDIBAPS), Hospital Clinic, University of Barcelona, Barcelona, Spain
- Lipid Clinic, Department of Endocrinology and Nutrition, Hospital Clínic, University of Barcelona, Barcelona, Spain
| | - Montserrat Fitó
- CIBER Physiopathology of Obesity and Nutrition (CIBERobn), Institute of Health Carlos III, Madrid, Spain
- Cardiovascular and Nutrition Research Group, Hospital del Mar Medical Research Institute, Barcelona, Spain
| | - Fernando Arós
- CIBER Physiopathology of Obesity and Nutrition (CIBERobn), Institute of Health Carlos III, Madrid, Spain
- Department of Cardiology, University Hospital of Alava, Vitoria, Spain
| | - Miquel Fiol
- CIBER Physiopathology of Obesity and Nutrition (CIBERobn), Institute of Health Carlos III, Madrid, Spain
- Institute of Health Sciences (IUNICS), University of Balearic Islands and Hospital Son Espases, Palma de Mallorca, Spain
| | - Lluís Serra-Majem
- CIBER Physiopathology of Obesity and Nutrition (CIBERobn), Institute of Health Carlos III, Madrid, Spain
- Research Institute of Biomedical and Health Sciences (IUIBS), University of Las Palmas de Gran Canaria, Las Palmas, Spain
| | - Clary B Clish
- Broad Institute of Massachusetts Institute of Technology and Harvard University, Cambridge, MA, USA
| | - Nerea Becerra-Tomás
- Universitat Rovira i Virgili, Biochemistry and Biotechnology Department, Human Nutrition Unit, Reus, Spain
- Pere i Virgili Health Research Institute (IISPV), Reus, Spain
- CIBER Physiopathology of Obesity and Nutrition (CIBERobn), Institute of Health Carlos III, Madrid, Spain
- Nutrition Unit, University Hospital of Sant Joan de Reus, Reus, Spain
| | - Miguel A Martínez-González
- CIBER Physiopathology of Obesity and Nutrition (CIBERobn), Institute of Health Carlos III, Madrid, Spain
- Department of Preventive Medicine and Public Health, University of Navarra, Pamplona, Spain
- Navarra Institute for Health Research (IdiSNA), Pamplona, Navarra, Spain
- Department of Nutrition, Harvard TH Chan School of Public Health, Boston, MA, USA
| | - Frank B Hu
- Department of Nutrition, Harvard TH Chan School of Public Health, Boston, MA, USA
- Department of Epidemiology, Harvard TH Chan School of Public Health, Boston, MA, USA
- Channing Division for Network Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
| | - Jordi Salas-Salvadó
- Universitat Rovira i Virgili, Biochemistry and Biotechnology Department, Human Nutrition Unit, Reus, Spain
- Pere i Virgili Health Research Institute (IISPV), Reus, Spain
- CIBER Physiopathology of Obesity and Nutrition (CIBERobn), Institute of Health Carlos III, Madrid, Spain
- Nutrition Unit, University Hospital of Sant Joan de Reus, Reus, Spain
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