Browsing by Author "Reyes, Pablo"

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    Evaluating the reliability of neurocognitive biomarkers of neurodegenerative diseases across countries: A machine learning approach
    (2020) Bachli, M. Belen; Sedeno, Lucas; Ochab, Jeremi K.; Piguet, Olivier; Kumfor, Fiona; Reyes, Pablo; Torralva, Teresa; Roca, María; Cardona, Juan Felipe; Gonzalez Campo, Cecilia; Herrera, Eduar; Slachevsky, Andrea; Matallana, Diana; Manes, Facundo; García, Adolfo M.; Ibanez, Agustín; Chialvo, Dante R.
    Accurate early diagnosis of neurodegenerative diseases represents a growing challenge for current clinical practice. Promisingly, current tools can be complemented by computational decision-support methods to objectively analyze multidimensional measures and increase diagnostic confidence. Yet, widespread application of these tools cannot be recommended unless they are proven to perform consistently and reproducibly across samples from different countries. We implemented machine-learning algorithms to evaluate the prediction power of neurocognitive biomarkers (behavioral and imaging measures) for classifying two neurodegenerative conditions –Alzheimer Disease (AD) and behavioral variant frontotemporal dementia (bvFTD)– across three different countries (>200 participants). We use machine-learning tools integrating multimodal measures such as cognitive scores (executive functions and cognitive screening) and brain atrophy volume (voxel based morphometry from fronto-temporo-insular regions in bvFTD, and temporo-parietal regions in AD) to identify the most relevant features in predicting the incidence of the diseases. In the Country-1 cohort, predictions of AD and bvFTD became maximally improved upon inclusion of cognitive screenings outcomes combined with atrophy levels. Multimodal training data from this cohort allowed predicting both AD and bvFTD in the other two novel datasets from other countries with high accuracy (>90%), demonstrating the robustness of the approach as well as the differential specificity and reliability of behavioral and neural markers for each condition. In sum, this is the first study, across centers and countries, to validate the predictive power of cognitive signatures combined with atrophy levels for contrastive neurodegenerative conditions, validating a benchmark for future assessments of reliability and reproducibility
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    Factores Asociados al Autoestigma de la Depresión en Adolescentes en Santiago, Chile.
    (2021) Suárez-Barba, Mariela Alexandra; Reyes, Pablo; Pérez Ewert, J. Carola; Martínez, Vania
    Resumen. Objetivo: Determinar la asociación entre autoestigma de la depresión y factores sociodemográficos, historia personal y parental de depresión, sintomatología ansiosa y depresiva, y calidad de vida en adolescentes. Método: Estudio transversal correlacional, en una muestra de 192 adolescentes (8º básico a 3º medio) de tres colegios particulares subvencionados de Santiago, Chile, se aplicaron cuestionarios de factores sociodemográficos, autoestigma de la depresión, sintomatología ansiosa y depresiva, y calidad de vida. Los datos se analizaron con prueba t de Student, ANOVA, coeficiente de Pearson y Regresión Lineal. Resultados: No hubo diferencias en autoestigma de depresión entre hombres y mujeres. Fue mayor el autoestigma de la depresión en adolescentes que sospechaban que habían tenido o tenían depresión, referían que su madre o padre habían tenido depresión, tenían mayor sintomatología depresiva y/o ansiosa y menor calidad de vida. Conclusión: La presencia de depresión en los progenitores progenitores (madre y/o padre), así como el desconocimiento de los adolescentes respecto a si ellos presentan el cuadro clínico, se relaciona con mayor autoestigma de la depresión en los adolescentes, lo que inhibe la búsqueda de ayuda.
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    Immunosensory signaling by carotid body chemoreceptors
    (2011) Zapata, Patricio; Larraín, Carolina; Reyes, Pablo; Fernández, Ricardo
    Injections of lipopolysaccharide (LPS) have been used to produce the signs of sepsis and study their underlying mechanisms. Intravenous (IV) injections of LPS in anesthetized cats induce tachypnea, tachycardia and hypotension, but ventilatory changes are suppressed after sectioning carotid and aortic nerves. Otherwise. LPS increases the basal frequency of carotid chemosensory discharges, but reduces ventilatory and chemosensory responses to hypoxia and nicotine injections. Increases in cytokines (IL-1 beta, IL-6 and TNF-alpha) are observed in plasma and tissues after injecting LPS. In carotid bodies perfused in vitro. TNF-alpha reduces chemosensory discharges induced by hypoxia. The rat carotid body and its sensory ganglion constitutively express LPS canonical receptor. TLR4, as well as TNF-alpha and its receptors (TNF-R1 and TNF-R2). Increases of TNF-alpha and TNF-R2 expression occur after LPS administration. The activation of peripheral and central autonomic pathways induced by LPS or IL's is partly dependent on intact vagus nerves. Thus, the carotid and vagus nerves provide routes between the immune system and CNS structures involved in systemic inflammatory responses. (C) 2011 Elsevier B.V. All rights reserved.
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    Mechanical and Antimicrobial Polyethylene Composites with CaO Nanoparticles
    (2020) Silva, Cristián; Bobillier, Felipe; Canales, Daniel; Sepúlveda, Francesca Antonella; Cament, Alejandro; Amigo, Nicolás; Rivas, Lina; Ulloa, María T.; Reyes, Pablo; Ortiz, J. Andrés; Gómez, Tatiana; Loyo, Carlos; Zapata, Paula A
    Low-density polyethylene composites containing different sizes of calcium oxide (CaO) nanoparticles were obtained by melt mixing. The CaO nanoparticles were synthesized by either the sol-gel or sonication methods, obtaining two different sizes: ca. 55 nm and 25 nm. These nanoparticles were used either as-synthesized or were modified organically on the surface with oleic acid (Mod-CaO), at concentrations of 3, 5, and 10 wt% in the polymer. The Mod-CaO nanoparticles of 25 nm can act as nucleating agents, increasing the polymer’s crystallinity. The Young’s Modulus increased with the Mod-CaO nanoparticles, rendering higher reinforcement effects with an increase as high as 36%. The reduction in Escherichia coli bacteria in the nanocomposites increased with the amount of CaO nanoparticles, the size reduction, and the surface modification. The highest antimicrobial behavior was found in the composites with a Mod-CaO of 25 nm, presenting a reduction of 99.99%. This strong antimicrobial effect can be associated with the release of the Ca2+ from the composites, as studied for the composite with 10 wt% nanoparticles. The ion release was dependent on the size of the nanoparticles and their surface modification. These findings show that CaO nanoparticles are an excellent alternative as an antimicrobial filler in polymer nanocomposites to be applied for food packaging or medical devices.
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    Multi-feature computational framework for combined signatures of dementia in underrepresented settings
    (2022) Moguilner, Sebastián; Birba, Agustina; Fittipaldi, Sol; Gonzalez, Cecilia; Tagliazucchi, Enzo; Reyes, Pablo; Matallana, Diana; Parra, Mario; Slachevsky Chonchol, Andrea; Farías, Gonzalo; Cruzat, Josefina; García, Adolfo; Eyre, Harris; La Joie, Renaud; Rabinovici, Gil; Whelan, Robert; Ibáñez, Agustín
    Objective.The differential diagnosis of behavioral variant frontotemporal dementia (bvFTD) and Alzheimer's disease (AD) remains challenging in underrepresented, underdiagnosed groups, including Latinos, as advanced biomarkers are rarely available. Recent guidelines for the study of dementia highlight the critical role of biomarkers. Thus, novel cost-effective complementary approaches are required in clinical settings.Approach. We developed a novel framework based on a gradient boosting machine learning classifier, tuned by Bayesian optimization, on a multi-feature multimodal approach (combining demographic, neuropsychological, magnetic resonance imaging (MRI), and electroencephalography/functional MRI connectivity data) to characterize neurodegeneration using site harmonization and sequential feature selection. We assessed 54 bvFTD and 76 AD patients and 152 healthy controls (HCs) from a Latin American consortium (ReDLat).Main results. The multimodal model yielded high area under the curve classification values (bvFTD patients vs HCs: 0.93 (±0.01); AD patients vs HCs: 0.95 (±0.01); bvFTD vs AD patients: 0.92 (±0.01)). The feature selection approach successfully filtered non-informative multimodal markers (from thousands to dozens).Results. Proved robust against multimodal heterogeneity, sociodemographic variability, and missing data.Significance. The model accurately identified dementia subtypes using measures readily available in underrepresented settings, with a similar performance than advanced biomarkers. This approach, if confirmed and replicated, may potentially complement clinical assessments in developing countries

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