Plan de cuidados para el paciente con Parkinson en tratamiento con L-Dopa intraduodenal

En 1817, James Parkinson describió por primera vez la enfermedad de Parkinson, quien la denominó"parálisis agitante" en alusión a los síntomas que provoca. Esta afección tiene una incidencia anual de 8-18 casos por cada 100.000 habitantes y afecta a personas mayores de 60 años, sin distinción sexual. Actualmente, no se dispone de ningún tratamiento médico ni quirúrgico que retrase su progresión. Por ello, el principal objetivo es intentar disminuir los síntomas y conseguir la independencia funcional del paciente. Los pacientes con Parkinson suelen recibir tratamiento a través de atención primaria y sólo recurren al hospital cuando presentan complicaciones de la enfermedad o para iniciar nuevas opciones de tratamiento. Uno de los tratamientos que se está utilizando actualmente es la administración de L-dopa intraduodenal a través de gastrostomía endoscópica percutánea. Esta opción de tratamiento se utiliza como alternativa al tratamiento con L-dopa en comprimidos cuando el paciente, tras una buena respuesta al tratamiento por vía oral (8-10 años), presenta un empeoramiento de la sintomatología que cursa con fluctuaciones motoras, en las que se alternan episodios de buena situación motora con incapacidad grave. En este artículo desarrollamos un plan de cuidados de un paciente con Parkinson en el que se ha decidido iniciar tratamiento con L-dopa intraduodenal. Entendemos que es importante conocer desde una óptica enfermera cuáles son los cuidados especiales que precisan este tipo de pacientes.

Parkinson"s disease DJ-1 L166P alters rRNA biogenesis by exclusion of TTRAP from the nucleolus and sequestration into cytoplasmic aggregates via TRAF6

Mutations in PARK7/DJ-1 gene are associated to autosomal recessive early onset forms of Parkinson"s disease (PD). Although large gene deletions have been linked to a loss-of-function phenotype, the pathogenic mechanism of missense mutations is less clear. The L166P mutation causes misfolding of DJ-1 protein and its degradation. L166P protein may also accumulate into insoluble cytoplasmic aggregates with a mechanism facilitated by the E3 ligase TNF receptor associated factor 6 (TRAF6). Upon proteasome impairment L166P activates the JNK/p38 MAPK apoptotic pathway by its interaction with TRAF and TNF Receptor Associated Protein (TTRAP). When proteasome activity is blocked in the presence of wild-type DJ-1, TTRAP forms aggregates that are localized to the cytoplasm or associated to nucleolar cavities, where it is required for a correct rRNA biogenesis. In this study we show that in post-mortem brains of sporadic PD patients TTRAP is associated to the nucleolus and to Lewy Bodies, cytoplasmic aggregates considered the hallmark of the disease. In SH-SY5Y neuroblastoma cells, misfolded mutant DJ-1 L166P alters rRNA biogenesis inhibiting TTRAP localization to the nucleolus and enhancing its recruitment into cytoplasmic aggregates with a mechanism that depends in part on TRAF6 activity. This work suggests that TTRAP plays a role in the molecular mechanisms of both sporadic and familial PD. Furthermore, it unveils the existence of an interplay between cytoplasmic and nucleolar aggregates that impacts rRNA biogenesis and involves TRAF6

Un estudi relaciona l'Alzheimer amb l'evolució del cervell humà

La recerca indica que la plasticitat del cervell té un doble vessant: és bàsica per a la intel·ligència humana, però també té efectes col·laterals, com la possible demència

Personalidad premórbida y factores de riesgo en la enfermedad de Alzheimer

El presente artículo hace un repaso de los principales estudios respecto a los factores de riesgo para la enfermedad de Alzheimer, priorizando los factores psicosociales y especialmente los que se refieren a la personalidad premórbida. Entre los factores psicosociales de riesgo, aparecen como los más destacados un bajo nivel educativo y una actividad-relación social restringida. Necesidad de protección, tutelaje y dependencia de otras personas, relación social e interpersonal restringida e introversión, son los elementos de riesgo más relevantes para la personalidad premórbida. Los factores que aparecen en los estudios mencionados tienen relación con la hipótesis de trabajo de la investigación que se desarrolla actualmente, acerca de los perfiles de riesgo en la personalidad premórbida. Esta hipótesis los sitúa en el campo de lo emocional y de la relación interpersonal: fragilidad de la identidad personal y sostenimiento del yo a través de una relación simbiótica con el otro.

GSK3 is involved in the relief of mitochondria pausing in a tau-dependent manner.

Mitochondrial trafficking deficits have been implicated in the pathogenesis of several neurological diseases, including Alzheimer's disease (AD). The Ser/Thre kinase GSK3β is believed to play a fundamental role in AD pathogenesis. Given that GSK3β substrates include Tau protein, here we studied the impact of GSK3β on mitochondrial trafficking and its dependence on Tau protein. Overexpression of GSK3β in neurons resulted in an increase in motile mitochondria, whereas a decrease in the activity of this kinase produced an increase in mitochondria pausing. These effects were dependent on Tau proteins, as Tau (−/−) neurons did not respond to distinct GSK3β levels. Furthermore, differences in GSK3β expression did not affect other parameters like mitochondria velocity or mitochondria run length. We conclude that GSK3B activity regulates mitochondrial axonal trafficking largely in a Tau-dependent manner.

Microbis per combatre els excessos de sucre

La microbiota intestinal dels diabètics és diferent. L'absència i l'excés d'alguns bacteris podrien estar darrere de la malaltia, indica un estudi a 'Nature'

Diagnosis of Alzheimer’s Disease from EEG by Means of Synchrony Measures in Optimized Frequency Bands

Several clinical studies have reported that EEG synchrony is affected by Alzheimer’s disease (AD). In this paper a frequency band analysis of AD EEG signals is presented, with the aim of improving the diagnosis of AD using EEG signals. In this paper, multiple synchrony measures are assessed through statistical tests (Mann–Whitney U test), including correlation, phase synchrony and Granger causality measures. Moreover, linear discriminant analysis (LDA) is conducted with those synchrony measures as features. For the data set at hand, the frequency range (5-6Hz) yields the best accuracy for diagnosing AD, which lies within the classical theta band (4-8Hz). The corresponding classification error is 4.88% for directed transfer function (DTF) Granger causality measure. Interestingly, results show that EEG of AD patients is more synchronous than in healthy subjects within the optimized range 5-6Hz, which is in sharp contrast with the loss of synchrony in AD EEG reported in many earlier studies. This new finding may provide new insights about the neurophysiology of AD. Additional testing on larger AD datasets is required to verify the effectiveness of the proposed approach.

Methylglyoxal Produced by Amyloid- Peptide-Induced Nitrotyrosination of Triosephosphate Isomerase Triggers Neuronal Death in Alzheimer’s Disease

Amyloid-β peptide (Aβ) aggregates induce nitro-oxidative stress, contributing to the characteristic neurodegeneration found in Alzheimer's disease (AD). One of the most strongly nitrotyrosinated proteins in AD is the triosephosphate isomerase (TPI) enzyme which regulates glycolytic flow, and its efficiency decreased when it is nitrotyrosinated. The main aims of this study were to analyze the impact of TPI nitrotyrosination on cell viability and to identify the mechanism behind this effect. In human neuroblastoma cells (SH-SY5Y), we evaluated the effects of Aβ42 oligomers on TPI nitrotyrosination. We found an increased production of methylglyoxal (MG), a toxic byproduct of the inefficient nitro-TPI function. The proapoptotic effects of Aβ42 oligomers, such as decreasing the protective Bcl2 and increasing the proapoptotic caspase-3 and Bax, were prevented with a MG chelator. Moreover, we used a double mutant TPI (Y165F and Y209F) to mimic nitrosative modifications due to Aβ action. Neuroblastoma cells transfected with the double mutant TPI consistently triggered MG production and a decrease in cell viability due to apoptotic mechanisms. Our data show for the first time that MG is playing a key role in the neuronal death induced by Aβ oligomers. This occurs because of TPI nitrotyrosination, which affects both tyrosines associated with the catalytic center.

Improving the Quality of EEG Data in Patients With Alzheimers Disease Using ICA

Does Independent Component Analysis (ICA) denature EEG signals? We applied ICA to two groups of subjects (mild Alzheimer patients and control subjects). The aim of this study was to examine whether or not the ICA method can reduce both group di®erences and within-subject variability. We found that ICA diminished Leave-One- Out root mean square error (RMSE) of validation (from 0.32 to 0.28), indicative of the reduction of group di®erence. More interestingly, ICA reduced the inter-subject variability within each group (¾ = 2:54 in the ± range before ICA, ¾ = 1:56 after, Bartlett p = 0.046 after Bonfer- roni correction). Additionally, we present a method to limit the impact of human error (' 13:8%, with 75.6% inter-cleaner agreement) during ICA cleaning, and reduce human bias. These ¯ndings suggests the novel usefulness of ICA in clinical EEG in Alzheimer's disease for reduction of subject variability.

ICA Cleaning procedure for EEG signals analysis: application to Alzheimer's disease detection

To develop systems in order to detect Alzheimer’s disease we want to use EEG signals. Available database is raw, so the first step must be to clean signals properly. We propose a new way of ICA cleaning on a database recorded from patients with Alzheimer's disease (mildAD, early stage). Two researchers visually inspected all the signals (EEG channels), and each recording's least corrupted (artefact-clean) continuous 20 sec interval were chosen for the analysis. Each trial was then decomposed using ICA. Sources were ordered using a kurtosis measure, and the researchers cleared up to seven sources per trial corresponding to artefacts (eye movements, EMG corruption, EKG, etc), using three criteria: (i) Isolated source on the scalp (only a few electrodes contribute to the source), (ii) Abnormal wave shape (drifts, eye blinks, sharp waves, etc.), (iii) Source of abnormally high amplitude ( �100 �V). We then evaluated the outcome of this cleaning by means of the classification of patients using multilayer perceptron neural networks. Results are very satisfactory and performance is increased from 50.9% to 73.1% correctly classified data using ICA cleaning procedure.

Alzheimer Disease Diagnosis based on Automatic Spontaneous Speech Analysis

Alzheimer’s disease (AD) is the most prevalent form of progressive degenerative dementia and it has a high socio-economic impact in Western countries, therefore is one of the most active research areas today. Its diagnosis is sometimes made by excluding other dementias, and definitive confirmation must be done trough a post-mortem study of the brain tissue of the patient. The purpose of this paper is to contribute to improvement of early diagnosis of AD and its degree of severity, from an automatic analysis performed by non-invasive intelligent methods. The methods selected in this case are Automatic Spontaneous Speech Analysis (ASSA) and Emotional Temperature (ET), that have the great advantage of being non invasive, low cost and without any side effects.

Spontaneous Speech and Emotional Response modeling based on One-class classifier oriented to Alzheimer Disease diagnosis

The purpose of our project is to contribute to earlier diagnosis of AD and better estimates of its severity by using automatic analysis performed through new biomarkers extracted from non-invasive intelligent methods. The methods selected in this case are speech biomarkers oriented to Sponta-neous Speech and Emotional Response Analysis. Thus the main goal of the present work is feature search in Spontaneous Speech oriented to pre-clinical evaluation for the definition of test for AD diagnosis by One-class classifier. One-class classifi-cation problem differs from multi-class classifier in one essen-tial aspect. In one-class classification it is assumed that only information of one of the classes, the target class, is available. In this work we explore the problem of imbalanced datasets that is particularly crucial in applications where the goal is to maximize recognition of the minority class as in medical diag-nosis. The use of information about outlier and Fractal Dimen-sion features improves the system performance.

Online drawings for dementia diagnose: in-air and pressure information analysis

In this paper we present experimental results comparing on-line drawings for control population (left and right hand) as well as Alzheimer disease patients. The drawings have been acquired by means of a digitizing tablet, which acquires time information angles and pressures. Experimental measures based on pressure and in-air movements appear to be significantly different for both groups, even when control population performs the tasks with the non-dominant hand.

Gene Set Analysis for improving genetic association studies

Introduction. Genetic epidemiology is focused on the study of the genetic causes that determine health and diseases in populations. To achieve this goal a common strategy is to explore differences in genetic variability between diseased and nondiseased individuals. Usual markers of genetic variability are single nucleotide polymorphisms (SNPs) which are changes in just one base in the genome. The usual statistical approach in genetic epidemiology study is a marginal analysis, where each SNP is analyzed separately for association with the phenotype. Motivation. It has been observed, that for common diseases the single-SNP analysis is not very powerful for detecting genetic causing variants. In this work, we consider Gene Set Analysis (GSA) as an alternative to standard marginal association approaches. GSA aims to assess the overall association of a set of genetic variants with a phenotype and has the potential to detect subtle effects of variants in a gene or a pathway that might be missed when assessed individually. Objective. We present a new optimized implementation of a pair of gene set analysis methodologies for analyze the individual evidence of SNPs in biological pathways. We perform a simulation study for exploring the power of the proposed methodologies in a set of scenarios with different number of causal SNPs under different effect sizes. In addition, we compare the results with the usual single-SNP analysis method. Moreover, we show the advantage of using the proposed gene set approaches in the context of an Alzheimer disease case-control study where we explore the Reelin signal pathway.

El fill de mare diabètica: un experiment de la Natura

Del fill de mare diabètica (FMD) s´ha dit que es tracta d'un autèntic 'experiment de la natura' per tractar-se d'un ésser que al llarg dels seus creixement i desenvolupament intrauterins es relaciona amb un medi ambient diferent al d'una gestació normal. Enfront d'aquesta anomalia, l'embrió primer i el fetus més tard no resten passius, sinó que generen una resposta adaptativa al medi estrany arribant a un altre nivell d'homeostasi però definitivament compensadora de la nova situació. Ara bé, en néixer i 'normalitzar-se' l'ambient, es fa palesa la malaltia...