Efecto de la amitriptilina sobre la evitación inhibitoria en ratones machos y hembras

RESUMEN Los antidepresivos son uno de los posibles tratamientos para prevenir y tratar los síntomas depresivos. Sin embargo, estos fármacos también pueden tener otros efectos no terapéuticos derivados de su acción sobre determinados sistemas de neurotransmisión, por ejemplo, sobre el sistema colinérgico, de gran importancia en los procesos de aprendizaje y memoria. Para mejorar el conocimiento del perfil cognitivo del antidepresivo amitriptilina se investigaron los efectos derivados de su administración aguda y crónica sobre el condicionamiento de evitación inhibitoria en ratones machos y hembras. Mediante esta técnica conductual, los animales aprenden en un único ensayo (entrenamiento) que cruzar del compartimiento iluminado (donde son situados) al oscuro supone recibir un estímulo aversivo (una descarga eléctrica); puestos de nuevo ante la misma situación (test), los ratones muestran estar condicionados si evitan cruzar al compartimiento oscuro. Todos los animales controles aprendieron el condicionamiento de evitación inhibitoria y, por eso, las latencias del test aumentaron en comparación con las del entrenamiento realizado a las 24 horas del entrenamiento. Sin embargo, la administración aguda de distintas dosis de amitriptilina (7.5, 15, 30 y 35 mg/kg) impidió, según el sexo, la adquisición y la consolidación de dicha tarea cuando se administró antes del entrenamiento e inmediatamente después del mismo, respectivamente. El tratamiento crónico de amitriptilina antes del entrenamiento (30 mg/kg) también deterioró dicho condicionamiento, pero no tuvo efectos cuando la administración comenzó 24 horas después del entrenamiento. Contrarrestar los efectos de la amitriptilina sobre la memoria con la administración previa al entrenamiento de un facilitador cognitivo (el nootropo piracetán con la dosis de 100 mg/kg), sólo se observó en los ratones machos y con la administración postentrenamiento del psicoestimulante cafeína (1 mg/kg), no hubo efectos en ningún sexo. Con la exploración del laberinto elevado en cruz durante 5 minutos, se interpretó que la inmovilidad mostrada en el condicionamiento de evitación inhibitoria no se debía a los efectos del antidepresivo amitriptilina sobre la ansiedad o la actividad sino sobre los procesos de memoria. Los resultados obtenidos en esta tesis doctoral tienen dos grandes similitudes con lo que se observa en los seres humanos y es que: (1) la amitriptilina tiene efectos negativos en la memoria en comparación con otros fármacos, como también se ha observado en los pacientes deprimidos y muestras de voluntarios y (2) estos efectos negativos sobre los procesos de memoria no se observan o se muestran menos si el aprendizaje sobre el que actúan está ya consolidado. __________________________________________________________________________________________________ SUMMARY Antidepressants are widely prescribed for depression and other disorders like anxiety. Apart from their therapeutic action, these psychotropic medications have side effects. For instance, tricyclic antidepressants have anticholinergic actions considered responsible for learning and memory impairment processes. With the aim of assess amitriptylines effects on memory here we studied its acute and chronic administration on a inhibitory avoidance task in male and female mice. Animals can learn in a sole session (training) that crossing from black side into dark side imply an electric shock; twenty-four hours later (test), control mice avoid crossing to dark side. In the case of treated mice, in both sexes, acute amitriptyline administration before or immediately after training blocks the inhibitory avoidance acquisition and consolidation, respectively. Chronic daily administration before training also impair this task, but there was absence of effects when the daily treatment started 24 hours after training. Prevention of amitriptyline-induced avoidance impairment by piracetam pre-training (chronic or acute administration) was posible in male but not female mice. Post-training acute administration of caffeine didnt produce any effect in any sex. In the elevated plus-maze exploration, amitriptyline had no effect on anxiety and in some acute doses reduced the activity. The results indicated that amitriptyline cognitive effects were not be mediated by anxiolytic effects

Anomaly Detection from Low-dimensional Latent Manifolds with Home Environmental Sensors

Human Activity Recognition poses a significant challenge within Active and Assisted Living (AAL) systems, relying extensively on ubiquitous environmental sensor-based acquisition devices to detect user situations in their daily living. Environmental measurement systems deployed indoors yield multiparametric data in heterogeneous formats, which presents a challenge for developing Machine Learning-based AAL models. We hypothesized that anomaly detection algorithms could be effectively employed to create data-driven models for monitoring home environments and that the complex multiparametric indoor measurements can often be represented by a relatively small number of latent variables generated through Manifold Learning (MnL) techniques. We examined both linear (Principal Component Analysis) and non-linear (AutoEncoders) techniques for generating these latent spaces and the utility of core domain detection techniques for identifying anomalies within the resulting low-dimensional manifolds. We benchmarked this approach using three publicly available datasets (hh105, Aruba, and Tulum) and one proprietary dataset (Elioth) for home environmental monitoring. Our results demonstrated the following key findings: (a) Nonlinear manifold estimation techniques offer significant advantages in retrieving latent variables when compared to linear techniques; (b) The quality of the reconstruction of the original multidimensional recordings serves as an acceptable indicator of the quality of the generated latent spaces; (c) Domain detection identifies regions of normality consistent with typical individual activities in these spaces; And (d) the system effectively detects deviations from typical activity patterns and labels anomalies. This study lays the groundwork for further exploration of enhanced methods for extracting information from MnL data models and their application within the AAL and possibly other sectors

Generalization and Regularization for Inverse Cardiac Estimators

Electrocardiographic Imaging (ECGI) aims to estimate the intracardiac potentials noninvasively, hence allowing the clinicians to better visualize and understand many arrhythmia mechanisms. Most of the estimators of epicardial potentials use a signal model based on an estimated spatial transfer matrix together with Tikhonov regularization techniques, which works well specially in simulations, but it can give limited accuracy in some real data. Based on the quasielectrostatic potential superposition principle, we propose a simple signal model that supports the implementation of principled out-of-sample algorithms for several of the most widely used regularization criteria in ECGI problems, hence improving the generalization capabilities of several of the current estimation methods. Experiments on simple cases (cylindrical and Gaussian shapes scrutinizing fast and slow changes, respectively) and on real data (examples of torso tank measurements available from Utah University, and an animal torso and epicardium measurements available from Maastricht University, both in the EDGAR public repository) show that the superposition-based out-of-sample tuning of regularization parameters promotes stabilized estimation errors of the unknown source potentials, while slightly increasing the re-estimation error on the measured data, as natural in non-overfitted solutions. The superposition signal model can be used for designing adequate out-of-sample tuning of Tikhonov regularization techniques, and it can be taken into account when using other regularization techniques in current commercial systems and research toolboxes on ECG

Inhibitory avoidance with a two-way shuttle-box

Evitación inhibitoria con una caja de escape-evitación d e dos sentidos. Se estudió, en treinta y cinco ratones macho OF1, la posibilidad de ejecutar experimentos de evitación inhibitoria, también llamada evitación pasiva, con una caja de escape-evitación de dos sentidos. Se empleó shock de dos niveles de intensidad (0.3 mA y 0.6 mA) y un tercer grupo de animales que no recibió shock. Se observó condicionamiento de evitación inhibitoria en el grupo de 0.6 mA (diferencias estadísticamente significativas entre las latencias de respuesta del Día 2 con respecto a las del Día 1) pero no en el grupo de 0.3 mA. Nuestros resultados permiten concluir que es posible obtener condicionamiento de evitación inhibitoria con una caja de escape-evitación de dos sentidos

Noise Maps for Quantitative and Clinical Severity Towards Long-Term ECG Monitoring

Noise and artifacts are inherent contaminating components and are particularly present in Holter electrocardiogram (ECG) monitoring. The presence of noise is even more significant in long-term monitoring (LTM) recordings, as these are collected for several days in patients following their daily activities; hence, strong artifact components can temporarily impair the clinical measurements from the LTM recordings. Traditionally, the noise presence has been dealt with as a problem of non-desirable component removal by means of several quantitative signal metrics such as the signal-to-noise ratio (SNR), but current systems do not provide any information about the true impact of noise on the ECG clinical evaluation. As a first step towards an alternative to classical approaches, this work assesses the ECG quality under the assumption that an ECG has good quality when it is clinically interpretable. Therefore, our hypotheses are that it is possible (a) to create a clinical severity score for the effect of the noise on the ECG, (b) to characterize its consistency in terms of its temporal and statistical distribution, and (c) to use it for signal quality evaluation in LTM scenarios. For this purpose, a database of external event recorder (EER) signals is assembled and labeled from a clinical point of view for its use as the gold standard of noise severity categorization. These devices are assumed to capture those signal segments more prone to be corrupted with noise during long-term periods. Then, the ECG noise is characterized through the comparison of these clinical severity criteria with conventional quantitative metrics taken from traditional noise-removal approaches, and noise maps are proposed as a novel representation tool to achieve this comparison. Our results showed that neither of the benchmarked quantitative noise measurement criteria represent an accurate enough estimation of the clinical severity of the noise. A case study of long-term ECG is reported, showing the statistical and temporal correspondences and properties with respect to EER signals used to create the gold standard for clinical noise. The proposed noise maps, together with the statistical consistency of the characterization of the noise clinical severity, paves the way towards forthcoming systems providing us with noise maps of the noise clinical severity, allowing the user to process different ECG segments with different techniques and in terms of different measured clinical parameters

On the Beat Detection Performance in Long-Term ECG Monitoring Scenarios

Despite the wide literature on R-wave detection algorithms for ECG Holter recordings, the long-term monitoring applications are bringing new requirements, and it is not clear that the existing methods can be straightforwardly used in those scenarios. Our aim in this work was twofold: First, we scrutinized the scope and limitations of existing methods for Holter monitoring when moving to long-term monitoring; Second, we proposed and benchmarked a beat detection method with adequate accuracy and usefulness in long-term scenarios. A longitudinal study was made with the most widely used waveform analysis algorithms, which allowed us to tune the free parameters of the required blocks, and a transversal study analyzed how these parameters change when moving to different databases. With all the above, the extension to long-term monitoring in a database of 7-day Holter monitoring was proposed and analyzed, by using an optimized simultaneous-multilead processing. We considered both own and public databases. In this new scenario, the noise-avoid mechanisms are more important due to the amount of noise that exists in these recordings, moreover, the computational efficiency is a key parameter in order to export the algorithm to the clinical practice. The method based on a Polling function outperformed the others in terms of accuracy and computational efficiency, yielding 99.48% sensitivity, 99.54% specificity, 99.69% positive predictive value, 99.46% accuracy, and 0.85% error for MIT-BIH arrhythmia database. We conclude that the method can be used in long-term Holter monitoring systems

Spectral Analysis and Mutual Information Estimation of Left and Right Intracardiac Electrograms during Ventricular Fibrillation

Ventricular fibrillation (VF) signals are characterized by highly volatile and erratic electrical impulses, the analysis of which is difficult given the complex behavior of the heart rhythms in the left (LV) and right ventricles (RV), as sometimes shown in intracardiac recorded Electrograms (EGM). However, there are few studies that analyze VF in humans according to the simultaneous behavior of heart signals in the two ventricles. The objective of this work was to perform a spectral and a non-linear analysis of the recordings of 22 patients with Congestive Heart Failure (CHF) and clinical indication for a cardiac resynchronization device, simultaneously obtained in LV and RV during induced VF in patients with a Biventricular Implantable Cardioverter Defibrillator (BICD) Contak Renewal IVTM (Boston Sci.). The Fourier Transform was used to identify the spectral content of the first six seconds of signals recorded in the RV and LV simultaneously. In addition, measurements that were based on Information Theory were scrutinized, including Entropy and Mutual Information. The results showed that in most patients the spectral envelopes of the EGM sources of RV and LV were complex, different, and with several frequency peaks. In addition, the Dominant Frequency (DF) in the LV was higher than in the RV, while the Organization Index (OI) had the opposite trend. The entropy measurements were more regular in the RV than in the LV, thus supporting the spectral findings. We can conclude that basic stochastic processing techniques should be scrutinized with caution and from basic to elaborated techniques, but they can provide us with useful information on the biosignals from both ventricles during VF