Indeed, we find that even within the stable coding scheme, memories drift during maintenance. When averaged across trials, such drift contributes to the width of the error distribution.In August 2012, a wildlife biologist became severely ill after becoming infected with a novel paramyxovirus, termed Sosuga virus. In the weeks prior to illness, the patient worked with multiple species of bats in South Sudan and Uganda, including Egyptian rousette bats (ERBs Rousettus aegyptiacus). A follow-up study of Ugandan bats found multiple wild-caught ERBs to test positive for SOSV in liver and spleen. To determine the competency of these bats to act as a natural reservoir host for SOSV capable of infecting humans, captive-bred ERBs were inoculated with a recombinant SOSV, representative of the patient's virus sequence. The bats were inoculated subcutaneously, sampled daily (blood, urine, fecal, oral and rectal swabs) and serially euthanized at predetermined time points. All inoculated bats became infected with SOSV in multiple tissues and blood, urine, oral, rectal and fecal swabs tested positive for SOSV RNA. No evidence of overt morbidity or mortality were observed in infected ERBs, although histopathological examination showed subclinical disease in a subset of tissues. Importantly, SOSV was isolated from oral/rectal swabs, urine and feces, demonstrating shedding of infectious virus concomitant with systemic infection. All bats euthanized at 21 days post-inoculation (DPI) seroconverted to SOSV between 16 and 21 DPI. These results are consistent with ERBs being competent reservoir hosts for SOSV with spillover potential to humans.Mendelian randomization (MR) implemented through instrumental variables analysis is an increasingly popular causal inference tool used in genetic epidemiology. But it can have limitations for evaluating simultaneous causal relationships in complex data sets that include, for example, multiple genetic predictors and multiple potential risk factors associated with the same genetic variant. Here we use real and simulated data to investigate Bayesian network analysis (BN) with the incorporation of directed arcs, representing genetic anchors, as an alternative approach. A Bayesian network describes the conditional dependencies/independencies of variables using a graphical model (a directed acyclic graph) with an accompanying joint probability. In real data, we found BN could be used to infer simultaneous causal relationships that confirmed the individual causal relationships suggested by bi-directional MR, while allowing for the existence of potential horizontal pleiotropy (that would violate MR assumptions). In simulated data, BN with two directional anchors (mimicking genetic instruments) had greater power for a fixed type 1 error than bi-directional MR, while BN with a single directional anchor performed better than or as well as bi-directional MR. Both BN and MR could be adversely affected by violations of their underlying assumptions (such as genetic confounding due to unmeasured horizontal pleiotropy). BN with no directional anchor generated inference that was no better than by chance, emphasizing the importance of directional anchors in BN (as in MR). Under highly pleiotropic simulated scenarios, BN outperformed both MR (and its recent extensions) and two recently-proposed alternative approaches a multi-SNP mediation intersection-union test (SMUT) and a latent causal variable (LCV) test. We conclude that BN incorporating genetic anchors is a useful complementary method to conventional MR for exploring causal relationships in complex data sets such as those generated from modern "omics" technologies.Targeted cancer therapies are powerful alternatives to chemotherapies or can be used complementary to these. Yet, the response to targeted treatments depends on a variety of factors, including mutations and expression levels, and therefore their outcome is difficult to predict. Here, we develop a mechanistic model of gastric cancer to study response and resistance factors for cetuximab treatment. The model captures the EGFR, ERK and AKT signaling pathways in two gastric cancer cell lines with different mutation patterns. We train the model using a comprehensive selection of time and dose response measurements, and provide an assessment of parameter and prediction uncertainties. We demonstrate that the proposed model facilitates the identification of causal differences between the cell lines. Furthermore, our study shows that the model provides predictions for the responses to different perturbations, such as knockdown and knockout experiments. Among other results, the model predicted the effect of MET mutations on cetuximab sensitivity. These predictive capabilities render the model a basis for the assessment of gastric cancer signaling and possibly for the development and discovery of predictive biomarkers.in English, Spanish Los medicamentos constituyen un bien económico que forma parte del gasto público y privado y de la toma de decisiones en salud. El aseguramiento de su calidad, eficacia y seguridad resulta fundamental. Sin embargo, la variada oferta disponible en el mercado chileno, donde se reconocen productos innovadores y genéricos, constituye un escenario confuso para consumidores y proveedores en salud. En esta revisión pretendemos aclarar los conceptos de fármacos bioequivalentes (aplicable a compuestos de tamaño molecular pequeño) y fármacos biosimilares (para compuestos biológicos de mayor complejidad molecular). En ambos casos, el comportamiento en el organismo del principio activo debe ser demostrado mediante estudios realizados para este fin. Una aplicación directa del concepto de bioequivalencia es la intercambiabilidad, definida como la posibilidad de utilizar un producto de un mismo principio activo, mientras la forma farmacéutica y esquema de dosificación sean iguales. Las normas relativas acas en torno a los productos farmacéuticos bioequivalentes y biosimilares en nuestro país.in English, Spanish Introducción En la enseñanza de la ética clínica se han utilizado numerosos métodos tradicionales que persiguen el desarrollo de competencias frente a los desafíos éticos actuales. Estas situaciones pueden ser reproducidas en forma estandarizadas mediante la simulación clínica para ser presentadas y evaluadas en el proceso de formación de los profesionales de salud. Sin embargo, se requiere disponer de evidencias sobre su efectividad. Objetivo Identificar y sintetizar la evidencia disponible sobre la efectividad de la enseñanza de la ética clínica usando la simulación como herramienta de aprendizaje.  https://www.selleckchem.com/products/sb290157-tfa.html  Métodos Revisión bibliográfica, con búsqueda en bases de datos PubMed, LILACS y Cochrane usando palabras clave en idiomas inglés y español "Ethics, Clinical/education" [Mesh]) AND "Simulation Training" [Mesh], sin filtros metodológicos, publicados desde el inicio de cada base de datos hasta julio de 2019, sin restricciones idiomáticas, geográficas o temporales, considerando como desenlace primario la identificación, resolución o reflexión de problemas éticos.