10 results on '"Rubio,G"'
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2. Genome Wide Meta-Analysis identifies common genetic signatures shared by heart function and Alzheimer’s disease
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Sáez, María Eugenia, González-Pérez, A., Hernández-Olasagarre, B., Beà, A., Moreno-Grau, Sonia., De Rojas, Itziar, Monté-Rubio, G., Orellana, Adelina, Valero, S., Comella i Carnicé, Joan Xavier, Sanchís, D., Ruiz, A., Universitat Autònoma de Barcelona, Institut Català de la Salut, [Sáez ME, González-Pérez A] Andalusian Bioinformatics Research Centre (CAEBi), Seville, Spain. [Hernández-Olasagarre B] Research Center and Memory Clinic, Fundació ACE. Institut Català de Neurociències Aplicades-Universitat Internacional de Catalunya (UIC), Barcelona, Spain. [Beà A] Universitat de Lleida – IRBLleida, Lleida, Spain. [Moreno-Grau S, de Rojas I] Research Center and Memory Clinic, Fundació ACE. Institut Català de Neurociències Aplicades-Universitat Internacional de Catalunya (UIC), Barcelona, Spain. Centro de Investigación Biomédica en Red sobre Enfermedades Neurodegenerativas (CIBERNED), ISCIII, 28031, Madrid, Spain. [Comella JX] Centro de Investigación Biomédica en Red sobre Enfermedades Neurodegenerativas (CIBERNED), ISCIII, 28031, Madrid, Spain. Vall d’Hebron Institut de Recerca (VHIR), Barcelona, Spain, and Vall d'Hebron Barcelona Hospital Campus
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Male ,0301 basic medicine ,Nervous System Diseases::Central Nervous System Diseases::Brain Diseases::Dementia::Alzheimer Disease [DISEASES] ,Echocardiogram ,lcsh:Medicine ,Cognitive decline ,Apoptosis ,Disease ,Genome ,0302 clinical medicine ,lcsh:Science ,Multidisciplinary ,Molecular medicine ,Disease genetics ,Alzheimer's ,Phenotype ,Heart Disease ,Meta-analysis ,Female ,Adult ,Genetic Markers ,Adolescent ,Heart Diseases ,Investigative Techniques::Epidemiologic Methods::Epidemiologic Research Design::Genome-Wide Association Study [ANALYTICAL, DIAGNOSTIC AND THERAPEUTIC TECHNIQUES, AND EQUIPMENT] ,Computational biology ,Biology ,Polymorphism, Single Nucleotide ,Article ,Young Adult ,03 medical and health sciences ,Meta-Analysis as Topic ,Alzheimer Disease ,Cor -- Fisiologia ,Humans ,Genetic Predisposition to Disease ,Genomes ,Gene ,lcsh:R ,Alzheimer, Malaltia d' ,Genòmica ,030104 developmental biology ,enfermedades del sistema nervioso::enfermedades del sistema nervioso central::enfermedades cerebrales::demencia::enfermedad de Alzheimer [ENFERMEDADES] ,Genetic Loci ,Genetic marker ,Genome wide Meta-analysis ,técnicas de investigación::métodos epidemiológicos::diseño de la investigación epidemiológica::estudio de asociación genómica completa [TÉCNICAS Y EQUIPOS ANALÍTICOS, DIAGNÓSTICOS Y TERAPÉUTICOS] ,lcsh:Q ,030217 neurology & neurosurgery ,Imputation (genetics) ,Genome-Wide Association Study - Abstract
Echocardiography has become an indispensable tool for the study of heart performance, improving the monitoring of individuals with cardiac diseases. Diverse genetic factors associated with echocardiographic measures have been previously reported. The impact of several apoptotic genes in heart development identified in experimental models prompted us to assess their potential association with human cardiac function. This study aimed at investigating the possible association of variants of apoptotic genes with echocardiographic traits and to identify new genetic markers associated with cardiac function. Genome wide data from different studies were obtained from public repositories. After quality control and imputation, a meta-analysis of individual association study results was performed. Our results confirmed the role of caspases and other apoptosis related genes with cardiac phenotypes. Moreover, enrichment analysis showed an over-representation of genes, including some apoptotic regulators, associated with Alzheimer’s disease. We further explored this unexpected observation which was confirmed by genetic correlation analyses. Our findings show the association of apoptotic gene variants with echocardiographic indicators of heart function and reveal a novel potential genetic link between echocardiographic measures in healthy populations and cognitive decline later on in life. These findings may have important implications for preventative strategies combating Alzheimer’s disease. General. Data collection and sharing for this project was partially funded by the Alzheimer’s Disease Neuroimaging Initiative (ADNI) (National Institutes of Health Grant U01 AG024904) and DOD ADNI (Department of Defense award number W81XWH-12-2-0012). ADNI is funded by the National Institute on Aging, the National Institute of Biomedical Imaging and Bioengineering, and through generous contributions from the following: AbbVie, Alzheimer’s Association; Alzheimer’s Drug Discovery Foundation; Araclon Biotech; BioClinica, Inc.; Biogen; Bristol-Myers Squibb Company; CereSpir, Inc.; Cogstate; Eisai Inc.; Elan Pharmaceuticals, Inc.; Eli Lilly and Company; EuroImmun; F. Hoffmann-La Roche Ltd and its affiliated company Genentech, Inc.; Fujirebio; GE Healthcare; IXICO Ltd.; Janssen Alzheimer Immunotherapy Research & Development, LLC.; Johnson & Johnson Pharmaceutical Research & Development LLC.; Lumosity; Lundbeck; Merck & Co., Inc.; Meso Scale Diagnostics, LLC.; NeuroRx Research; Neurotrack Technologies; Novartis Pharmaceuticals Corporation; Pfizer Inc.; Piramal Imaging; Servier; Takeda Pharmaceutical Company; and Transition Therapeutics. The Canadian Institutes of Health Research is providing funds to support ADNI clinical sites in Canada. Private sector contributions are facilitated by the Foundation for the National Institutes of Health (www.fnih.org). The grantee organization is the Northern California Institute for Research and Education, and the study is coordinated by the Alzheimer’s Therapeutic Research Institute at the University of Southern California. ADNI data are disseminated by the Laboratory for Neuro Imaging at the University of Southern California. For the Alzheimer’s Disease Neuroimaging Initiative: Data used in preparation of this article were obtained from the Alzheimer’s Disease Neuroimaging Initiative (ADNI) database (adni.loni.usc.edu). As such, the investigators within the ADNI contributed to the design and implementation of ADNI and/or provided data but did not participate in analysis or writing of this report. A complete listing of ADNI investigators can be found at: http://adni.loni.usc.edu/wp19content/uploads/how_to_apply/ADNI_Acknowledgement_List.pdf. The AddNeuroMed data are from a public-private partnership supported by EFPIA companies and SMEs as part of InnoMed (Innovative Medicines in Europe), an Integrated Project funded by the European Union of the Sixth Framework program priority FP6-2004-LIFESCIHEALTH-5. Clinical leads responsible for data collection are Iwona Kłoszewska (Lodz), Simon Lovestone (London), Patrizia Mecocci (Perugia), Hilkka Soininen (Kuopio), Magda Tsolaki (Thessaloniki), and Bruno Vellas (Toulouse), imaging leads are Andy Simmons (London), Lars-Olad Wahlund (Stockholm) and Christian Spenger (Zurich) and bioinformatics leads are Richard Dobson (London) and Stephen Newhouse (London). This dataset was downloaded from Synapse (https://doi.org/10.7303/syn2790911). Funding support for the Alzheimer’s Disease Genetics Consortium (ADGC) was provided through the NIA Division of Neuroscience (U01-AG032984). This study was downloaded from NIH dbGaP repository (phs000372.v1). The Coronary Artery Risk Development in Young Adults Study (CARDIA) is conducted and supported by the National Heart, Lung, and Blood Institute (NHLBI) in collaboration with the University of Alabama at Birmingham (N01-HC95095 & N01-HC48047), University of Minnesota (N01-HC48048), Northwestern University (N01-HC48049), and Kaiser Foundation Research Institute (N01-HC48050). This manuscript was not approved by CARDIA. The opinions and conclusions contained in this publication are solely those of the authors, and are not endorsed by CARDIA or the NHLBI and should not be assumed to reflect the opinions or conclusions of either. Genotyping for the CARDIA GENEVA cohort was supported by grant U01 HG004729 from the National Human Genome Research Institute. This study was downloaded from NIH dbGaP repository (phs000285.v3.p2). The Cardiovascular Heart Study (CHS) was supported by contracts HHSN268201200036C, HHSN268200800007C, N01-HC85079, N01-HC-85080, N01-HC-85081, N01-HC-85082, N01-HC-85083, N01-HC-85084, N01-HC-85085, N01-HC-85086, N01-HC-35129, N01 HC-15103, N01 HC-55222, N01-HC-75150, N01-HC-45133, and N01-HC-85239; grant numbers U01 HL080295 and U01 HL130014 from the National Heart, Lung, and Blood Institute, and R01 AG-023629 from the National Institute on Aging, with additional contribution from the National Institute of Neurological Disorders and Stroke. A full list of principal CHS investigators and institutions can be found at https://chs-nhlbi.org/pi. This manuscript was not prepared in collaboration with CHS investigators and does not necessarily reflect the opinions or views of CHS or the NHLBI. Support for the genotyping through the CARe Study was provided by NHLBI Contract N01-HC-65226. This study was downloaded from NIH dbGaP repository (phs000287.v5.p1). The Framingham Heart Study is conducted and supported by the National Heart, Lung, and Blood Institute (NHLBI) in collaboration with Boston University (Contract No. N01-HC-25195 and HHSN268201500001I). This manuscript was not prepared in collaboration with investigators of the Framingham Heart Study and does not necessarily reflect the opinions or views of the Framingham Heart Study, Boston University, or NHLBI. “Funding for SHARe Affymetrix genotyping was provided by NHLBI Contract N02-HL64278. SHARe Illumina genotyping was provided under an agreement between Illumina and Boston University. Funding for Affymetrix genotyping of the FHS Omni cohorts was provided by Intramural NHLBI funds from Andrew D. Johnson and Christopher J. O’Donnell. This dataset was obtained from the NIH dbGaP repository (phs000007.v29.p10). The genotypic and associated phenotypic data used in the study, “Multi-Site Collaborative Study for Genotype-Phenotype Associations in Alzheimer’s Disease (GenADA)” were provided by the GlaxoSmithKline, R&D Limited. The datasets used for analyses described in this manuscript were obtained from NIH dbGaP repository (phs000219.v1.p1). The Mayo Clinic Alzheimer’s Disease Genetic Studies, led by Dr. Nilüfer Ertekin-Taner and Dr. Steven G. Younkin, Mayo Clinic, Jacksonville, FL using samples from the Mayo Clinic Study of Aging, the Mayo Clinic Alzheimer’s Disease Research Center, and the Mayo Clinic Brain Bank. Data collection was supported through funding by NIA grants P50 AG016574, R01 AG032990, U01 AG046139, R01 AG018023, U01 AG006576, U01 AG006786, R01 AG025711, R01 AG017216, R01 AG003949, NINDS grant R01 NS080820, CurePSP Foundation, and support from Mayo Foundation. This dataset was downloaded from Synapse (https://doi.org/10.7303/syn5550404). The MESA study was supported by contracts HHSN268201500003I, N01-HC-95159, N01-HC-95160, N01-HC-95161, N01-HC-95162, N01-HC-95163, N01-HC-95164, N01-HC-95165, N01-HC-95166, N01-HC-95167, N01-HC-95168 and N01-HC-95169 from the National Heart, Lung, and Blood Institute, and by grants UL1-TR-000040, UL1-TR-001079, and UL1-TR-001420 from NCATS. The authors thank the other investigators, the staff, and the participants of the MESA study for their valuable contributions. A full list of participating MESA investigators and institutions can be found at http://www.mesa-nhlbi.org. This dataset was obtained from the NIH dbGaP repository (phs000209.v6.p2). The Neocodex-Murcia study was funded by the Fundación Alzheimur (Murcia), the Ministerio de Educación y Ciencia (Gobierno de España), Corporación Tecnológica de Andalucía and Agencia IDEA (Consejería de Innovación, Junta de Andalucía). The Diabetes Research Laboratory, Biomedical Research Foundation. University Hospital Clínico San Carlos has been supported by CIBER de Diabetes y Enfermedades Metabólicas Asociadas (CIBERDEM); CIBERDEM is an ISCIII Project. The ROS/MAP study data were provided by the Rush Alzheimer’s Disease Center, Rush University Medical Center, Chicago. Data collection was supported through funding by NIA grants P30AG10161, R01AG15819, R01AG17917, R01AG30146, R01AG36836, U01AG32984, U01AG46152, the Illinois Department of Public Health, and the Translational Genomics Research Institute. This dataset was downloaded from Synapse (https://doi.org/10.7303/syn3219045). The TGEN study was supported by Kronos Life Sciences Laboratories, the National Institute on Aging (Arizona Alzheimer’s Disease Center P30 AG19610, RO1 AG023193, Mayo Clinic Alzheimer’s Disease Center P50 AG16574, and Intramural Research Program), the National Alzheimer’s Coordinating Center (U01 AG016976), and the state of Arizona. TGEN investigators provided free access to genotype data to other researchers via Coriell Biorepositories (http://www.coriell.org). The results published here are in part based on data obtained from the AMP-AD Knowledge Portal accessed at https://doi.org/10.7303/syn2580853. D.S. research is supported by Grant 20153810 from Fundació La Marató de TV3 and Grant SAF2013-44942-R from the Ministerio de Economía y Competitividad (MINECO) and, with J.X.C., Grant 2009SGR-346 from the Agència de Gestió d’Ajuts Universitaris i de Recerca (AGAUR) from the Government of Catalonia. A.B. has a predoctoral contract from Fundació La Marató de TV3. A.R. research is also supported by grants PI13/02434 and PI16/01861. Acción Estratégica en Salud, integrated in the Spanish National R&D&I Plan and financed by ISCIII (Instituto de Salud Carlos III)-Subdirección General de Evaluación and the European Regional Development Fund (ERDF – “A way to make Europe”), by Fundación banca “La Caixa” and Grifols SA (GR@ACE project). This work was also partly supported by the ADAPTED consortium, which has received funding from the Innovative Medicines Initiative 2 Joint Undertaking under grant agreement No 115975. This Joint Undertaking receives support from the European Union’s Horizon 2020 research and innovation program and the European Federation of Pharmaceutical Industries and Associations.
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3. Impact of COVID-19 first wave on the mental health of healthcare workers in a Front-Line Spanish Tertiary Hospital: lessons learned.
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Molina JD, Amigo F, Vilagut G, Mortier P, Muñoz-Ruiperez C, Rodrigo Holgado I, Juanes González A, Combarro Ripoll CE, Alonso J, and Rubio G
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- Humans, Female, Male, Mental Health, Tertiary Care Centers, Cross-Sectional Studies, Pandemics, Health Personnel, Personnel, Hospital, Anxiety epidemiology, Depression, Depressive Disorder, Major epidemiology, COVID-19 epidemiology, Substance-Related Disorders
- Abstract
Healthcare workers (HCWs) were at high risk of experiencing psychological distress during COVID-19 pandemic. The objective of this study was to evaluate the impact on HCWs' mental health in a Spanish hospital. Cross-sectional study of HCW, active between May and June 2020. A web-based survey assessed probable current mental disorders (major depressive disorder [PHQ-8 ≥ 10], generalized anxiety disorder [GAD-7 ≥ 10], panic attacks, post-traumatic stress disorder [PTSD; PLC-5 ≥ 7], or substance use disorder [CAGE-AID ≥ 2]). The Sheehan Disability Scale (SDS) was used to assess severe impairment and items taken from the modified self-report version of the Columbia Suicide Severity Rating Scale (C-SSRS) assessed suicidal thoughts and behaviors. A total of 870 HCWs completed the survey. Most frequent probable mental disorders were major depressive disorder (33.6%), generalized anxiety disorder (25.5%), panic attacks (26.9%), PTSD (27.2%), and substance use disorder (5.0%). Being female, having aged 18-29 years, being an auxiliary nurse, direct exposure to COVID-19-infected patients, and pre-pandemic lifetime mental disorders were positively associated with mental issues. Hospital HCWs presented a high prevalence of symptoms of mental disorders, especially depression, PTSD, panic attacks, and anxiety. Younger individuals and those with lifetime mental disorders have been more vulnerable to experiencing them., (© 2024. The Author(s).)
- Published
- 2024
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4. Subsoil-potassium depletion accounts for the nutrient budget in high-potassium agricultural soils.
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Correndo AA, Rubio G, García FO, and Ciampitti IA
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Continuous potassium (K) removal without replenishment is progressively mining Argentinean soils. Our goals were to evaluate the sensitivity of soil-K to K budgets, quantify soil-K changes over time along the soil profile, and identify soil variables that regulate soil-K depletion. Four on-farm trials under two crop rotations including maize, wheat and soybean were evaluated. Three treatments were compared: (1) control (no fertilizer applied); (2) application of nitrogen, phosphorus, and sulfur fertilizers -NPS-; and (3) pristine condition. After nine years, crops removed from 258 to 556 kg K ha
-1 . Only two sites showed a decline in the exchangeable-K levels at 0-20 cm but unrelated to K budget. Topsoil exchangeable-K levels under agriculture resulted 48% lower than their pristine conditions, although still above response levels. Both soil exchangeable-K and slowly-exchangeable K vertical distribution patterns (0-100 cm) displayed substantial depletion relative to pristine conditions, mainly concentrated at subsoil (20-100 cm), with 55-83% for exchangeable-K, and 74-95% for slowly-exchangeable-K. Higher pristine levels of exchangeable-K and slowly-exchangeable-K and lower clay and silt contents resulted in higher soil-K depletion. Soil K management guidelines should consider both topsoil and subsoil nutrient status and variables related to soil K buffer capacity.- Published
- 2021
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5. Subtle executive deficits are associated with higher brain amyloid burden and lower cortical volume in subjective cognitive decline: the FACEHBI cohort.
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Pérez-Cordón A, Monté-Rubio G, Sanabria A, Rodriguez-Gomez O, Valero S, Abdelnour C, Marquié M, Espinosa A, Ortega G, Hernandez I, Rosende-Roca M, Vargas L, Mauleón A, Gil S, Tartari JP, Lomeña F, Campos F, Vivas A, Gomez-Chiari M, Benaque A, Ruiz A, Tárraga L, Boada M, and Alegret M
- Subjects
- Aged, Aged, 80 and over, Alzheimer Disease diagnosis, Alzheimer Disease pathology, Brain diagnostic imaging, Brain pathology, Cognitive Dysfunction diagnosis, Cognitive Dysfunction pathology, Cohort Studies, Early Diagnosis, Female, Humans, Male, Middle Aged, Positron Emission Tomography Computed Tomography, Up-Regulation, Alzheimer Disease metabolism, Amyloid beta-Peptides metabolism, Brain metabolism, Cognitive Dysfunction metabolism, Executive Function physiology
- Abstract
To determine whether lower performance on executive function tests in subjective cognitive decline (SCD) individuals are associated with higher levels of brain amyloid beta (Aβ) deposition and regional volumetric reduction in areas of interest for Alzheimer's disease (AD). 195 individuals with SCD from the FACEHBI study were assessed with a neuropsychological battery that included the following nine executive function tests: Trail Making Test A and B (TMTA, TMTB), the Rule Shift Cards subtest of BADS, the Automatic Inhibition subtest of the Syndrom Kurz Test (AI-SKT), Digit Span Backwards and Similarities from WAIS-III, and the letter, semantic, and verb fluency tests. All subjects underwent an 18F-Florbetaben positron emission tomography (FBB-PET) scan to measure global standard uptake value ratio (SUVR), and a magnetic resonance imaging (MRI). A multiple regression analysis, adjusted for age, was carried out to explore the association between global SUVR and performance on executive tests. Then, on those tests significantly associated with amyloid burden, a voxel-based morphometry (VBM) analysis was carried out to explore their correlates with grey matter volume. Multiple regression analysis revealed a statistically significant association between Aβ deposition and performance on one of the executive tests (the AI-SKT). Moreover, VBM analysis showed worse AI-SKT scores were related to lower volume in bilateral hippocampus and left inferior frontal regions. In conclusion, in SCD individuals, worse automatic inhibition ability has been found related to higher cerebral Aβ deposition and lower volume in the hippocampus and frontal regions. Thus, our results may contribute to the early detection of AD in individuals with SCD.
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- 2020
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6. Au@Ag Core-Shell Nanorods Support Plasmonic Fano Resonances.
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Peña-Rodríguez O, Díaz-Núñez P, González-Rubio G, Manzaneda-González V, Rivera A, Perlado JM, Junquera E, and Guerrero-Martínez A
- Abstract
In this work, we investigated experimentally and theoretically the plasmonic Fano resonances (FRs) exhibited by core-shell nanorods composed of a gold core and a silver shell (Au@Ag NRs). The colloidal synthesis of these Au@Ag NRs produces nanostructures with rich plasmonic features, of which two different FRs are particularly interesting. The FR with spectral location at higher energies (3.7 eV) originates from the interaction between a plasmonic mode of the nanoparticle and the interband transitions of Au. In contrast, the tunable FR at lower energies (2.92-2.75 eV) is ascribed to the interaction between the dominant transversal LSPR mode of the Ag shell and the transversal plasmon mode of the Au@Ag nanostructure. The unique symmetrical morphology and FRs of these Au@Ag NRs make them promising candidates for plasmonic sensors and metamaterials components.
- Published
- 2020
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7. Genetic variants in IL17A and serum levels of IL-17A are associated with COPD related to tobacco smoking and biomass burning.
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Ponce-Gallegos MA, Pérez-Rubio G, Ambrocio-Ortiz E, Partida-Zavala N, Hernández-Zenteno R, Flores-Trujillo F, García-Gómez L, Hernández-Pérez A, Ramírez-Venegas A, and Falfán-Valencia R
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- Adult, Aged, Aged, 80 and over, Case-Control Studies, Female, Genetic Association Studies, Humans, Logistic Models, Male, Middle Aged, Polymorphism, Single Nucleotide, Pulmonary Disease, Chronic Obstructive blood, Pulmonary Disease, Chronic Obstructive etiology, Tobacco Smoking blood, Tobacco Smoking epidemiology, Tobacco Smoking genetics, Up-Regulation, Interleukin-17 blood, Interleukin-17 genetics, Pulmonary Disease, Chronic Obstructive genetics, Smoke adverse effects, Tobacco Smoking adverse effects
- Abstract
IL-17A is an important pro-inflammatory cytokine involved in the inflammatory response in chronic obstructive pulmonary disease (COPD). To evaluate the role played by single nucleotide polymorphisms of IL17A and protein levels in susceptibility to COPD, 1,807 subjects were included in a case-control study; 436 had COPD related to tobacco smoking (COPD-S) and 190 had COPD related to biomass burning (COPD-BB). Six hundred fifty-seven smokers without COPD (SWOC) and 183 biomass burning-exposed subjects (BBES) served as the respective control groups. The CC genotype and C allele of rs8193036 were associated with COPD (COPD-S vs. SWOC: p < 0.05; OR = 3.01, and OR = 1.28, respectively), as well as a recessive model (p < 0.01; OR = 2.91). Significant differences in serum levels were identified between COPD-S vs. SWOC, COPD-S vs. COPD-BB, and SWOC vs. BBES (p < 0.01). By comparing genotypes in the COPD-BB group TT vs. CC and TC vs. CC (p < 0.05), we found lower levels for the CC genotype. Logistic regression analysis by co-variables was performed, keeping the associations between COPD-S vs. SWOC with both polymorphisms evaluated (p < 0.05), as well as in COPD-BB vs. BBES but with a reduced risk of exacerbation (p < 0.05). In conclusion, polymorphisms in IL17A are associated with COPD. Serum levels of IL-17A were higher in smokers with and without COPD.
- Published
- 2020
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8. On the Large Near-Field Enhancement on Nanocolumnar Gold Substrates.
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Díaz-Núñez P, García-Martín JM, González MU, González-Arrabal R, Rivera A, Alonso-González P, Martín-Sánchez J, Taboada-Gutiérrez J, González-Rubio G, Guerrero-Martínez A, Bañares L, and Peña-Rodríguez O
- Abstract
One of the most important and distinctive features of plasmonic nanostructures is their ability to confine large electromagnetic fields on nanometric volumes; i.e., the so-called hot spots. The generation, control and characterization of the hot spots are fundamental for several applications, like surface-enhanced spectroscopies. In this work, we characterize the near-field distribution and enhancement of nanostructured gold thin films fabricated by glancing angle deposition magnetron sputtering. These films are composed of columnar nanostructures with high roughness and high density of inter-columnar gaps, where the electromagnetic radiation can be confined, generating hot spots. As expected, the hot spots are localized in the gaps between adjacent nanocolumns and we use scattering-type scanning near-field optical microscopy to image their distribution over the surface of the samples. The experimental results are compared with finite-difference time-domain simulations, finding an excellent agreement between them. The spectral dependence of the field-enhancement is also studied with the simulations, together with surface-enhanced Raman spectroscopy at different excitation wavelengths in the visible-NIR range, proving a broad-band response of the substrates. These findings may result in interesting applications in the field of surface-enhanced optical spectroscopies or sensing.
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- 2019
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9. Visual impairment in aging and cognitive decline: experience in a Memory Clinic.
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Marquié M, Castilla-Martí M, Valero S, Martínez J, Sánchez D, Hernández I, Rosende-Roca M, Vargas L, Mauleón A, Rodríguez-Gómez O, Abdelnour C, Gil S, Santos-Santos MA, Alegret M, Espinosa A, Ortega G, Pérez-Cordón A, Sanabria Á, Roberto N, Moreno-Grau S, de Rojas I, Simó R, Ciudin A, Hernández C, Orellana A, Monté-Rubio G, Benaque A, Ruiz A, Tárraga L, and Boada M
- Subjects
- Aged, Aged, 80 and over, Cognitive Dysfunction diagnosis, Cohort Studies, Dementia diagnosis, Dementia physiopathology, Female, Humans, Intraocular Pressure physiology, Logistic Models, Male, Middle Aged, Neuropsychological Tests statistics & numerical data, Outpatient Clinics, Hospital, Quality of Life, Tomography, Optical Coherence methods, Vision Disorders diagnosis, Visual Acuity physiology, Aging, Cognitive Dysfunction physiopathology, Memory physiology, Vision Disorders physiopathology
- Abstract
Visual impairment is common in people living with dementia and regular ophthalmological exams may improve their quality of life. We evaluated visual function in a cohort of elderly individuals and analyzed its association with their degree of cognitive impairment. Participants underwent neurological and neuropsychological exams, neuro-ophthalmological assessment (visual acuity, intraocular pressure, rates of past ophthalmological pathologies, use of ocular correction, treatments and surgeries) and optical coherence tomography (OCT) scan. We analyzed differences in ophthalmological characteristics among diagnostic groups. The final sample of 1746 study participants aged ≥ 50 comprised 229 individuals with Subjective Cognitive Decline (SCD), 695 with mild cognitive impairment (MCI) and 833 with Dementia (Alzheimer disease: n = 660; vascular dementia: n = 92, Lewy body dementia: n = 34; frontotemporal dementia: n = 19 and other: n = 28). Age, gender and education were used as covariates. Patients with Dementia, compared to those with SCD and MCI, presented worse visual acuity (p < 0.001), used less visual correction (p = 0.02 and p < 0.001, respectively) and fewer ophthalmological treatments (p = 0.004 and p < 0.001, respectively) and underwent fewer ocular surgeries (p = 0.009 and p < 0.001, respectively). OCT image quality worsened in parallel to cognitive decline (Dementia vs SCD: p = 0.008; Dementia vs MCI: p < 0.001). No group differences in past ophthalmological disorders or abnormal OCT findings were detected. Efforts should be made to ensure dementia patients undergo regular ophthalmological assessments to correct their visual function in order to improve their quality of life.
- Published
- 2019
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10. The Spanish version of Face-Name Associative Memory Exam (S-FNAME) performance is related to amyloid burden in Subjective Cognitive Decline.
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Sanabria A, Alegret M, Rodriguez-Gomez O, Valero S, Sotolongo-Grau O, Monté-Rubio G, Abdelnour C, Espinosa A, Ortega G, Perez-Cordon A, Gailhajanet A, Hernandez I, Rosende-Roca M, Vargas L, Mauleon A, Sanchez D, Martin E, Rentz DM, Lomeña F, Ruiz A, Tarraga L, and Boada M
- Subjects
- Activities of Daily Living, Aged, Aged, 80 and over, Cognitive Dysfunction diagnostic imaging, Cognitive Dysfunction metabolism, Female, Humans, Male, Middle Aged, Positron-Emission Tomography, Amyloid beta-Peptides metabolism, Cognitive Dysfunction physiopathology, Language, Memory, Neuropsychological Tests
- Abstract
The Face-Name Associative Memory Exam (FNAME) is a paired associative memory test created to detect memory deficits in individuals with preclinical Alzheimer's disease (AD). Worse performance on FNAME in cognitively healthy individuals were found related to higher amyloid beta (Aβ) burden measured with Positron-Emission-Tomography using
11 C-PiB (PiB-PET). We previously reported normative data of a Spanish version of FNAME (S-FNAME) in cognitively healthy Spanish-speaking subjects. The aim of the present study was to determine whether performance on S-FNAME was associated with Aβ burden in subjective cognitive decline (SCD) individuals. 200 SCD subjects received neurological and neuropsychological assessments, including the S-FNAME and the Word List task from the Wechsler-Memory-Scale-III (WMS-III). Moreover, they received an MRI and (18)F-Florbetaben Positron-Emission-Tomography (FBB-PET) to measure Aβ burden. Three cognitive factor composites were derived for the episodic memory measures (face-name [SFN-N], face-occupation [SFN-O] and WMS-III) to determine whether episodic memory performance was related to Aβ deposition. Higher global Aβ deposition was significantly related to worse performance on SFN-N but not with SFN-O or WMS-III Composite. Moreover, worse SFN-N performance was significantly related to higher Aβ deposition in bilateral Posterior Cingulate Cortex. The S-FNAME may be a promising neuropsychological tool for detecting SCD individuals with preclinical AD.- Published
- 2018
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