Bayesian regression analysis of data with random effects covariates from nonlinear longitudinal measurements

© 2015 Elsevier Inc. Joint models for a wide class of response variables and longitudinal measurements consist on a mixed-effects model to fit longitudinal trajectories whose random effects enter as covariates in a generalized linear model for the primary response. They provide a useful way to assess association between these two kinds of data, which in clinical studies are often collected jointly on a series of individuals and may help understanding, for instance, the mechanisms of recovery of a certain disease or the efficacy of a given therapy. When a nonlinear mixed-effects model is used to fit the longitudinal trajectories, the existing estimation strategies based on likelihood approximations have been shown to exhibit some computational efficiency problems (De la Cruz et al., 2011). In this article we consider a Bayesian estimation procedure for the joint model with a nonlinear mixed-effects model for the longitudinal data and a generalized linear model for the primary response. The proposed prior structure allows for the implementation of an MCMC sampler. Moreover, we consider that the errors in the longitudinal model may be correlated. We apply our method to the analysis of hormone levels measured at the early stages of pregnancy that can be used to predict normal versus abnormal pregnancy outcomes. We also conduct a simulation study to assess the importance of modelling correlated errors and quantify the consequences of model misspecification

Deporte escolar: factores psico-socio-estructurales que lo determinan

Esta propuesta está dirigida a agentes relacionados con el deporte educativo, que a través de sus valores, recompensas y estilos de retroalimentación, configuran el contexto deportivo dándole una forma distinta en cada caso. Ellos ofrecen oportunidades para decidir, cometer errores sin consecuencias, volver a intentarlo, tomar conciencia de las propias posibilidades y para otras muchas cosas más. Son estas, entre otras, las razones que nos llevan a defender este planteamiento.Proposamen hau kirol hezigarriarekin zerikusia duten eragileentzat da; horiek beren balio, sari eta berrelikadura estiloen bidez kirol testuingurua itxuratzen baitute, kasu bakoitzean molde desberdina ematen diotela. Horiek aukerak ematen dituzte erabakiak hartzeko, ondoriorik gabeko hutsak egiteko, berriro saiatzeko, nork bere ahalbideez kontzientzia hartzeko, bai eta beste gauza askotarako ere. Horiek dira, besteak beste, planteamendu hau defendatzera eramaten gaituzten arrazoiak.Cette proposition est adressée aux agents en relation avec le sport éducatif, qui, à travers ses valeurs, récompenses et styles de retroalimentation, configurent le contexte sportif en lui donnant une forme différence dans chaque cas. Ils offrent des occasions pour décider, commettre des erreurs sans conséquences, recommencer, prendre conscience des propres possibilités et pour beaucoup d'autres choses. Ce sont, entre autres, les raisons qui nous amènent à défendre ce programme.This article addresses the educational features of sport. It is directed to those sport agents who through transmission of values, establishment of rewards and by using optimal feedback styles articulate the educational sport context. This context in turn, offers opportunities to make decisions, to commit errors without negative consequences and allowing new trials, to become aware of one's competence.... These are some of the issues underlying this article

Predicting Pregnancy Outcomes Using Longitudinal Information: A Penalized Splines Mixed–Effects Model Approach

We propose a semiparametric mixed–effects model (SNMM) using penalized splines to clas- sify longitudinal data and improve the prediction of a binary outcome. The work is motivated by a study in which different hormone levels were measured during the early stages of preg- nancy, and the challenge is using this information to predict normal versus abnormal pregnancy outcomes. The aim of this paper is to compare models and estimation strategies based on alternative formulations of SNMMs depending on the characteristics of the data set under con- sideration. For our motivating example, we address the classification problem using a particular case of the SNMM in which the parameter space has a finite dimensional component (fixed effects and variance components) and an infinite dimensional component (unknown function) that need to be estimated. The nonparametric component of the model is estimated using pe- nalized splines. For the parametric component, we compare the advantages of using random effects versus direct modeling of the correlation structure of the errors. Numerical studies show that our approach improves over other existing methods for the analysis of this type of data. Furthermore, the results obtained using our method support the idea that explicit modeling of the serial correlation of the error term improves the prediction accuracy with respect to a model with random effects, but independent errors.MTM2014-52184-

EXPLORING THE IMPACT OF APOE POLYMORPHISM ON THE MOLECULAR, MORPHOLOGICAL AND FUNCTIONAL PROFILE OF iPSC-DERIVED ASTROCYTES FROM ALZHEIMER'S PATIENTS

Comunicación presentada a FENS Forum 2022Alzheimer¿s disease (AD) is pathologically characterised by the presence of amyloid-beta plaques, neurofibrillary tangles containing hyperphosphorylated Tau protein, neuroinflammation and neuronal death leading to progressive cognitive impairment. The ¿4 allele of the gene encoding apolipoprotein E (APOE), which is mainly expressed in glial cells, is the strongest genetic risk factor for sporadic AD. Increasing evidence has shown that APOE4 may disrupt normal astrocyte activity, potentially contributing to AD pathology, but the impact of different APOE alleles on astrocyte differentiation, maturation and function is not yet fully understood. To go in depth on these questions, we obtained induced pluripotent stem cells (iPSCs) from fibroblasts of AD patients carrying ¿3 and ¿4 alleles (in homozygosis) and from healthy patients. We also used gene-edited iPSC lines homozygous for the main APOE variants and an APOE knock-out line. iPSC-derived human astrocytes were generated by establishing a differentiation protocol through the consecutive addition of small molecules and growth factors, and the expression of typical markers (GFAP, GLT1, AQP4 and S100beta) and APOE was analysed. In addition, astrocytes exhibited functional features like glutamate uptake capacity and calcium waves production. They also responded to an inflammatory stimulus (IL-1beta and TNF-alpha) or to the presence of amyloid-beta 1-42 peptide by changing their morphology and increasing the expression levels of pro-inflammatory factors and cytokines. Our results shed light on the potential dual role of APOE polymorphism and the individual¿s genetic background in favouring or perhaps preventing AD pathology

ANALYSING THE MOLECULAR, MORPHOLOGICAL AND FUNCTIONAL PROFILE OF iPSC-DERIVED ASTROCYTES FROM ALZHEIMER'S DISEASE PATIENTS

Comunicación presentada en Global Summit on Neurodegenerative Diseases NEURO 2020/22The ε4 allele of the gene encoding apolipoprotein E (APOE), which is mainly expressed in glial cells, is the strongest genetic risk factor for sporadic AD. Increasing evidence has shown that APOE4 may disrupt normal astrocyte activity, potentially contributing to AD pathology, but the impact of different APOE alleles on astrocyte maturation and function as well as their inflammatory profile is not yet fully understood. To answer these questions, we obtained induced pluripotent stem cells (iPSCs) from fibroblasts of AD patients carrying ε3 and ε4 alleles (in homozygosis) and from healthy patients. We also used gene-edited iPSC lines homozygous for the main APOE variants and an APOE knock-out line. iPSC-derived human astrocytes were generated through the consecutive addition of small molecules and growth factors to the culture medium, and the expression of typical markers (GFAP, GLT1, AQP4 and S100beta) was analysed. In addition, astrocytes exhibited functional features like glutamate uptake capacity and calcium waves. They also responded to an inflammatory stimulus (IL-1beta and TNF-alpha) or to the presence of amyloid-beta 1-42 peptide by changing their morphology and increasing the expression levels of pro-inflammatory factors and cytokines. Our results shed light on the potential dual role of APOE polymorphism and the individual's genetic background in favouring or perhaps preventing AD pathology

Modelo CBCRisk para determinar el riesgo de cáncer de mama contralateral en el cáncer de mama esporádico

Introducción La mayoría de los cánceres de mama (CM) se diagnostican en mujeres sin antecedentes familiares y no portadoras de mutaciones de riesgo. En las últimas décadas se ha producido un aumento de mastectomías profilácticas contralaterales (MPC) en estas pacientes. El CBCRisk es un modelo que calcula el riesgo absoluto de cáncer de mama contralateral (CMC) y pretende servir para el asesoramiento de pacientes con CM esporádico sobre la MPC. Método Análisis observacional retrospectivo de pacientes con un cáncer de mama esporádico sometidas a MPC durante 2017-2019. Análisis descriptivo, comparativo y de regresión logística univariante para identificar factores predictivos de LMAR y/o CMC oculto. Evaluación del modelo CBCRisk publicado en 2017 y distintos valores límite para la recomendación de MPC. Resultados Se seleccionaron 42 pacientes. Incidencia de LMAR y cáncer oculto (CO) menor que la descrita en la literatura (9, 52% LMAR, 2, 38% CO). Ninguna de las variables evaluadas alcanzó significación estadística para la predicción de lesiones. El valor de CBCRisk a cinco años medio en pacientes con hallazgos patológicos fue de 2, 08 (DE 0, 97), superior al CBCRisk medio del conjunto (1, 87 ± 0, 91) y del subgrupo de MPC sin hallazgos patológicos (1, 84 ± 0, 91). Solo el CBCRisk = 3 resultó significativo (p = 0, 04) para la predicción de hallazgos patológicos. Conclusión Las pacientes con CM esporádico deben ser adecuadamente informadas de los riesgos y beneficios estimados de la MPC. El CBCRisk puede ser útil para el asesoramiento de estas pacientes, pero precisa validación en cohortes más amplias y prospectivas. Introduction The great majority of breast cancer (BC) cases are diagnosed in women who have no known family history of the disease and are not carriers of any risk mutation. During the past few decades an increase in the number of contralateral prophylactic mastectomy (CPM) has been produced in these patients. The CBCRisk model calculates the absolute risk of suffering from contralateral breast cancer (CBC); thus, it can be used to counselling patients with sporadic breast cancer. Method An observational, retrospective study including sporadic breast cancer patients treated with contralateral prophylactic mastectomy has been conducted between 2017 and 2019. A descriptive and comparative study with one variation of logistic regression has been carried out in order to identify predictive factors of occult tumors (OT) and medium/high risk damage (MHRD). Evaluation of the CBCRisk model published in 2017 and different limit values for the CPM recommendation. Results 42 patients were selected. Incidence of MHRD and OT was lower than that described in the literatura (9.52% MHRD, 2.38% OT). None of the evaluated variables reached statistical significance for predicting injuries. The average value of CBCRisk 5 years ahead found in patients with pathological findings was 2.08 (SD 0.97), higher than the average value of the whole group (1.87 ± 0.91) and the subgroup without pathological findings (1.84 ± 0.91). Only values = 3 for CBCRisk were considered statistically significant (p = 0.04) for the prediction of histological lesions. Conclusion Patients with sporadic breast cancer should be adequately informed about the estimated risks and benefits of undergoing a contralateral prophylactic mastectomy. The CBCRisk may be useful for the counseling of these patients, but it requires validation in larger and prospective cohorts

Elucidating the role of shape anisotropy in faceted magnetic nanoparticles using biogenic magnetosomes as a model

Shape anisotropy is of primary importance to understand the magnetic behavior of nanoparticles, but a rigorous analysis in polyhedral morphologies is missing. In this work, a model based on finite element techniques has been developed to calculate the shape anisotropy energy landscape for cubic, octahedral, and truncated octahedral morphologies. In all cases, a cubic shape anisotropy is found that evolves to quasi uniaxial anisotropy when the nanoparticle is elongated amp; 8805;2 . This model is tested on magnetosomes, amp; 8764;45 nm truncated octahedral magnetite nanoparticles forming a chain inside Magnetospirillum gryphiswaldense MSR 1 bacteria. This chain presents a slightly bent helical configuration due to a 20 tilting of the magnetic moment of each magnetosome out of chain axis. Electron cryotomography images reveal that these magnetosomes are not ideal truncated octahedrons but present amp; 8776;7.5 extrusion of one of the 001 square faces and amp; 8776;10 extrusion of an adjacent 111 hexagonal face. Our model shows that this deformation gives rise to a quasi uniaxial shape anisotropy, a result of the combination of a uniaxial Ksh u 7 kJ m amp; 8722;3 and a cubic Ksh c 1.5 kJ m amp; 8722;3 contribution, which is responsible for the 20 tilting of the magnetic moment. Finally, our results have allowed us to accurately reproduce, within the framework of the Landau Lifshitz Gilbert model, the experimental AC loops measured for these magnetotactic bacteri