Closest horizons of Hsp70 engagement to manage neurodegeneration

Our review seeks to elucidate the current state-of-the-art in studies of 70-kilodalton-weighed heat shock proteins (Hsp70) in neurodegenerative diseases (NDs). The family has already been shown to play a crucial role in pathological aggregation for a wide spectrum of brain pathologies. However, a slender boundary between a big body of fundamental data and its implementation has only recently been crossed. Currently, we are witnessing an anticipated advancement in the domain with dozens of studies published every month. In this review, we briefly summarize scattered results regarding the role of Hsp70 in the most common NDs including Alzheimer’s disease (AD), Parkinson’s disease (PD), and amyotrophic lateral sclerosis (ALS). We also bridge translational studies and clinical trials to portray the output for medical practice. Available options to regulate Hsp70 activity in NDs are outlined, too

Closest horizons of Hsp70 engagement to manage neurodegeneration

Our review seeks to elucidate the current state-of-the-art in studies of 70-kilodalton-weighed heat shock proteins (Hsp70) in neurodegenerative diseases (NDs). The family has already been shown to play a crucial role in pathological aggregation for a wide spectrum of brain pathologies. However, a slender boundary between a big body of fundamental data and its implementation has only recently been crossed. Currently, we are witnessing an anticipated advancement in the domain with dozens of studies published every month. In this review, we briefly summarize scattered results regarding the role of Hsp70 in the most common NDs including Alzheimer’s disease (AD), Parkinson’s disease (PD), and amyotrophic lateral sclerosis (ALS). We also bridge translational studies and clinical trials to portray the output for medical practice. Available options to regulate Hsp70 activity in NDs are outlined, too

Closest horizons of Hsp70 engagement to manage neurodegeneration.

This is the final version. Available on open access from Frontiers Media via the DOI in this record. Our review seeks to elucidate the current state-of-the-art in studies of 70-kilodalton-weighed heat shock proteins (Hsp70) in neurodegenerative diseases (NDs). The family has already been shown to play a crucial role in pathological aggregation for a wide spectrum of brain pathologies. However, a slender boundary between a big body of fundamental data and its implementation has only recently been crossed. Currently, we are witnessing an anticipated advancement in the domain with dozens of studies published every month. In this review, we briefly summarize scattered results regarding the role of Hsp70 in the most common NDs including Alzheimer's disease (AD), Parkinson's disease (PD), and amyotrophic lateral sclerosis (ALS). We also bridge translational studies and clinical trials to portray the output for medical practice. Available options to regulate Hsp70 activity in NDs are outlined, too.Russian Science Foundatio

Strategies to gain novel Alzheimer’s disease diagnostics and therapeutics using modulators of ABCA transporters

Adenosine-triphosphate-(ATP)-binding cassette (ABC) transport proteins are ubiquitously present membrane-bound efflux pumps that distribute endo- and xenobiotics across intra- and intercellular barriers. Discovered over 40 years ago, ABC transporters have been identified as key players in various human diseases, such as multidrug-resistant cancer and atherosclerosis, but also neurodegenerative diseases, such as Alzheimer’s disease (AD). Most prominent and well-studied are ABCB1, ABCC1, and ABCG2, not only due to their contribution to the multidrug resistance (MDR) phenotype in cancer, but also due to their contribution to AD. However, our understanding of other ABC transporters is limited, and most of the 49 human ABC transporters have been largely neglected as potential targets for novel small-molecule drugs. This is especially true for the ABCA subfamily, which contains several members known to play a role in AD initiation and progression. This review provides up-to-date information on the proposed functional background and pathological role of ABCA transporters in AD. We also provide an overview of small-molecules shown to interact with ABCA transporters as well as potential in silico, in vitro, and in vivo methodologies to gain novel templates for the development of innovative ABC transporter-targeting diagnostics and therapeutics

Clasificadores basados en máquinas de soporte vertical para el diagnóstico y predicción de la enfermedas de Alzheimer

La enfermedad de Alzheimer (AD) es un desorden neurodegenerativo cuyo diagnóstico clinico es realizado después de excluir otros tipos de demencia y el diagnóstico clinico definitivo requiere además de la presencia de un alto decit cognitivo, la confirmación histológica mediante autopsia de la presencia de proteinas como las neurobras de tau ( ) y amyloid beta (A) en los tejidos cerebrales. AD es una de las enfermedades de mayor impacto social en Europa y América. En el pasado 2005, en Europa fueron diagnosticados 3.600.000 pacientes afectados por AD (fuente: Frost & Sullivan) y en una reciente investigación impulsada por la asociación Alzheimer Europe, se estima que 7.3 millones de personas padecen algún tipo de demencia. A pesar de que la ocurrencia de AD no es un suceso normal en la población mayor, el riesgo de desarrollar la enfermedad se incrementa en esa etapa.Postprint (published version

Clasificadores basados en máquinas de soporte vertical para el diagnóstico y predicción de la enfermedad de Alzheimer

En este trabajo, se estableció una metodología de soporte al diagnostico de AD, principalmente en sus etapas MCI ocasionado por AD y demencia ocasionada por AD. Para este fin fueron obtenidos casos clínicos de dos proyectos de investigación en demencia del tipo AD de reconocida trayectoria: las bases de datos Alzheimer's Disease Neuroimaging Initiative (ADNI) (www.loni.ucla.edu/ADNI) y la base de datos The Open Access Series of Imaging Studies (OASIS) (http://www.oasis-brains.org/). Asimismo, fueron establecidas dos tareas principales: la selección de variables predictoras de AD y la construcción de modelos de clasificacion basados en máquinas de soporte vectorial (SVM), entrenados a partir de las variables seleccionadas. Las variables predictoras seleccionadas estuvieron conformadas por biomarcadores morfométricos y características socio-demográficas y neuropsicológicas. Estas variables deberan ser útiles para la discriminación de casos clínicos en tres estados: (1) Estado normal (generalmente personas mayores sanas); (2) Estado MCI ocasionado por AD; y (3) Etapa de demencia ocasionada por AD. Por otro lado, los modelos SVM estarán enfocados a dos tareas principales: (1) Diagnóstico de AD mediante la discriminación entre sujetos sanos y sujetos con AD; y (2) Predicción de AD, orientada a la discriminación de sujetos MCI con riesgo de convertirse a AD y sujetos MCI sin riesgo de conversión. Asimismo, estos modelos deberán garantizar resultados aceptables, respecto a la sensibilidad y especificidad de las tareas de clasificación. Los resultados obtenidos en esta investigación son prometedores. Por un lado, el subconjunto de variables seleccionadas como relevantes para el diagnóstico de AD, tienen correlación con los resultados de investigaciones previas. Asimismo, en la etapa de testeo, los resultados demostraron que los modelos SVM son de gran utilidad para el soporte diagnóstico clínico de esta enfermedad, siendo capaces de discriminar sujetos con AD de sujetos sanos (diagnóstico) con una exactitud mayor al 99% y distinguir a los sujetos MCI con riesgo de conversión a AD de los sujetos MCI sin riego de conversión (predicción) con una exactitud superior al 94%