QSAR Modelling to Identify LRRK2 Inhibitors for Parkinson's Disease

Parkinson's disease is one of the most common neurodegenerative illnesses in older persons and the leucine-rich repeat kinase 2 (LRRK2) is an auspicious target for its pharmacological treatment. In this work, quantitative structure-activity relationship (QSAR) models for identification of putative inhibitors of LRRK2 protein are developed by using an in-house chemical library and several machine learning techniques. The methodology applied in this paper has two steps: first, alternative subsets of molecular descriptors useful for characterizing LRRK2 inhibitors are chosen by a multi-objective feature selection method; secondly, QSAR models are learned by using these subsets and three different strategies for supervised learning. The qualities of all these QSAR models are compared by classical metrics and the best models are discussed in statistical and physicochemical terms.Fil: Sebastián Pérez, Víctor. Consejo Superior de Investigaciones Científicas. Centro de Investigaciones Biológicas; EspañaFil: Martínez, María Jimena. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Instituto de Ciencias e Ingeniería de la Computación. Universidad Nacional del Sur. Departamento de Ciencias e Ingeniería de la Computación. Instituto de Ciencias e Ingeniería de la Computación; ArgentinaFil: Gil, Carmen. Consejo Superior de Investigaciones Científicas. Centro de Investigaciones Biológicas; EspañaFil: Campillo Martín, Nuria Eugenia. Consejo Superior de Investigaciones Científicas. Centro de Investigaciones Biológicas; EspañaFil: Martínez, Ana. Consejo Superior de Investigaciones Científicas. Centro de Investigaciones Biológicas; EspañaFil: Ponzoni, Ignacio. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Instituto de Ciencias e Ingeniería de la Computación. Universidad Nacional del Sur. Departamento de Ciencias e Ingeniería de la Computación. Instituto de Ciencias e Ingeniería de la Computación; Argentin

New applications for known drugs: Human glycogen synthase kinase 3 inhibitors as modulators of Aspergillus fumigatus growth [Postprint]

Invasive aspergillosis (IA) is one of the most severe forms of fungi infection. IA disease is mainly due to Aspergillus fumigatus, an air-borne opportunistic pathogen. Mortality rate caused by IA is still very high (50-95%), because of difficulty in early diagnostics and reduced antifungal treatment options, thus new and efficient drugs are necessary. The aim of this work is, using Aspergillus nidulans as non-pathogen model, to develop efficient drugs to treat IA. The recent discovered role of glycogen synthase kinase-3 homologue, GskA, in A. fumigatus human infection and our previous experience on human GSK-3 inhibitors focus our attention on this kinase as a target for the development of antifungal drugs. With the aim to identify effective inhibitors of colonial growth of A. fumigatus we use A. nidulans as an accurate model for in vivo and in silico studies. Several well-known human GSK-3β inhibitors were tested for inhibition of A. nidulans colony growth. Computational tools as docking studies and binding site prediction was used to explain the different biological profile of the tested inhibitors. Three of the five tested hGSK3β inhibitors are able to reduce completely the colonial growth by covalent bind to the enzyme. Therefore these compounds may be useful in different applications to eradicate IA.SAF2012-37979-C03-01 to A.M; BFU2012-33142 to E.A.EN

Operational modal analysis: a tool for assessing changes on structural health state of historical constructions after consolidation and reinforcement Works-Jura Chapel (Jerez de la Frontera, Spain)

Today’s society is sensitive to the architectural heritage conservation. This implies to perform works to maintain these buildings and to assure their structural security. In the last years, the structural analysis of historical masonry constructions has experienced a great progress, thanks to the use of techniques based on the study of the dynamic properties of building structures. In this context, changes on the structural health state of a building are one of the elements that can be assessed considering changes on their dynamic properties. This is useful to evaluate the effectiveness of structural interventions on this kind of buildings by analysing these properties before and after it. This paper focuses on the Jura Chapel, in Jerez de la Frontera (Spain). This chapel is part of San Juan de los Caballeros Church and is dated from the 15th century. In 2015 and after the identification of some structural damages in the chapel vault, an intervention was initiated to improve its structural behaviour and to recover its original appearance. The present work reports the evaluation of the effects that this intervention has on the structural health state of the building, using nondestructive techniques based on ambient vibration tests (AVT) and Operational Modal Analysis (OMA). The AVT were performed for both prerestored and restored states and under environmental loads. A discussion about the validity of doing AVT from extrados when a vault presents disconnection between ribs and web is included in the paper. As a result, the first five natural frequency values have increased while the corresponding mode shapes have not changed significantly. This proves a structural health improvement caused by the repairing process without changing the original behaviour of the structure. This work shows OMA capabilities for evaluating the effectiveness of intervention works on the health state of a historical masonry structure

FOOD PRODUCT ACCEPTANCE AND PREFERENCE PREDECTION THROUGH AUTOMATED FACIAL EXPRESSION ANALYSIS (MEDICIÓN DE ACEPTACIÓN Y PREFERENCIA DE PRODUCTOS ALIMENTICIOS MEDIANTE ANÁLISIS AUTOMATIZADO DE EXPRESIONES FACIALES)

ResumenSe presenta un sistema para determinar la aceptación y las preferencias de usuarios en productos alimenticios a través del reconocimiento de emociones. Los cambios en expresiones faciales de 80 sujetos mientras probaban cinco distintos productos alimenticios fueron capturados con el sensor Microsoft Kinect. Las expresiones faciales se contrastaron con las evaluaciones sensoriales de los consumidores. Para el reconocimiento de expresiones faciales en cada cuadro del video, se entrenó una red neuronal y se utilizaron diferentes técnicas de aprendizaje supervisado (como máquinas de soporte vectorial, perceptrón multicapa y árboles de regresión) para determinar que sabores podrían ser aceptados y rechazados por el consumidor.  Se decidió utilizar la red neuronal, y al observar la matriz de confusión se obtiene un porcentaje de reconocimiento adecuado para las siguientes emociones: neutral 94%, sorpesa 98%, felicidad 99% y disgusto 94%. La aplicación industrial es relevante en el sector de Investigación y Desarrollo de la industria de alimentos.Palabras Claves: aceptación de consumidores, análisis sensorial, aprendizaje de máquina, expresiones faciales, Kinect, visualización.AbstractThis paper presents a system for determining consumer acceptance and preferences of food products through emotion recognition. Changes in facial expressions of 80 test subjects while tasting five different food samples were captured using the Microsoft Kinect sensor. The expressions were compared to the consumers’ sensory evaluations. To determine the facial expressions in every video frame, a neural network was trained and different supervised learning techniques (such as support vector machines, multilayer perceptron and regression trees) were used to predict which of the different tastes could be accepted or rejected. A neuronal net was used, when observing the confusion matrix a percentage of adequate recognition was obtained for the following emotions: neutral (94%), surprise (98%), happiness (99%) and disgust (94%). The industrial application of the proposed system is relevant for the Food Industry Research and Development (R&D) by allowing the sampling of a product by potential consumers and analyzing their emotions before launching into market.Keywords: consumer’s acceptance, sensory analysis, facial expressions, Kinect, machine learning, visualization

Cancer-derived exosomes loaded with ultrathin palladium nanosheets for targeted bioorthogonal catalysis

The transformational impact of bioorthogonal chemistries has inspired new strategies for the in vivo synthesis of bioactive agents through non-natural means. Among these, Pd catalysts have played a prominent role in the growing subfield of bioorthogonal catalysis by producing xenobiotics and uncaging biomolecules in living systems. However, delivering catalysts selectively to specific cell types still lags behind catalyst development. Here, we have developed a bioartificial device comprising cancer-derived exosomes that are loaded with Pd catalysts by a method that enables the controlled assembly of Pd nanosheets directly inside the vesicles. This hybrid system mediates Pd-triggered dealkylation reactions in vitro and inside cells, and displays preferential tropism for their progenitor cells. The use of Trojan exosomes to deliver abiotic catalysts into designated cancer cells creates the opportunity for a new targeted therapy modality; that is, exosome-directed catalyst prodrug therapy, whose first steps are presented herein with the cell-specific release of the anticancer drug panobinostat

Leucine rich repeat kinase 2 (LRRK2) inhibitors based on indolinone scaffold: Potential pro-neurogenic agents

Leucine-rich repeat kinase 2 (LRRK2) is one of the most pursued targets for Parkinson's disease (PD) therapy. Moreover, it has recently described its role in regulating Wnt signaling and thus, it may be involved in adult neurogenesis. This new hypothesis could give rise to double disease-modifying agents firstly by the benefits of inhibiting LRRK2 and secondly by promoting adult neurogenesis. Herein we report, the design, synthesis, biological evaluation, SAR and potential binding mode of indoline-like LRRK2 inhibitors and their preliminary neurogenic effect in neural precursor cells isolated from adult mice ventricular-subventricular zone. These results open new therapeutic horizons for the use of LRRK2 inhibitors as neuroregenerative agents. Moreover, the indolinone derivatives here prepared, inhibitors of the kinase activity of LRRK2, may be considered as pharmacological probes to study the potential neuroregeneration of the damaged brain. (C) 2017 Elsevier Masson SAS. All rights reserved

QSAR Classification Models for Predicting the Activity of Inhibitors of Beta-Secretase (BACE1) Associated with Alzheimer’s Disease

Alzheimer’s disease is one of the most common neurodegenerative disorders in elder population. The β-site amyloid cleavage enzyme 1 (BACE1) is the major constituent of amyloid plaques and plays a central role in this brain pathogenesis, thus it constitutes an auspicious pharmacological target for its treatment. In this paper, a QSAR model for identification of potential inhibitors of BACE1 protein is designed by using classification methods. For building this model, a database with 215 molecules collected from different sources has been assembled. This dataset contains diverse compounds with different scaffolds and physical-chemical properties, covering a wide chemical space in the drug-like range. The most distinctive aspect of the applied QSAR strategy is the combination of hybridization with backward elimination of models, which contributes to improve the quality of the final QSAR model. Another relevant step is the visual analysis of the molecular descriptors that allows guaranteeing the absence of information redundancy in the model. The QSAR model performances have been assessed by traditional metrics, and the final proposed model has low cardinality, and reaches a high percentage of chemical compounds correctly classified.Fil: Ponzoni, Ignacio. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Instituto de Ciencias e Ingeniería de la Computación. Universidad Nacional del Sur. Departamento de Ciencias e Ingeniería de la Computación. Instituto de Ciencias e Ingeniería de la Computación; Argentina. Universidad Nacional del Sur. Departamento de Ciencias e Ingeniería de la Computación. Instituto de Ciencias e Ingeniería de la Computación; ArgentinaFil: Sebastián Pérez, Víctor. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Instituto de Ciencias e Ingeniería de la Computación. Universidad Nacional del Sur. Departamento de Ciencias e Ingeniería de la Computación. Instituto de Ciencias e Ingeniería de la Computación; Argentina. Consejo Superior de Investigaciones Científicas. Centro de Investigaciones Biológicas; EspañaFil: Martínez, María J.. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Instituto de Ciencias e Ingeniería de la Computación. Universidad Nacional del Sur. Departamento de Ciencias e Ingeniería de la Computación. Instituto de Ciencias e Ingeniería de la Computación; Argentina. Universidad Nacional del Sur. Departamento de Ciencias e Ingeniería de la Computación. Instituto de Ciencias e Ingeniería de la Computación; ArgentinaFil: Roca, Carlos. Consejo Superior de Investigaciones Científicas. Centro de Investigaciones Biológicas; EspañaFil: De la Cruz Pérez, Carlos. Consejo Superior de Investigaciones Científicas. Centro de Investigaciones Biológicas; EspañaFil: Cravero, Fiorella. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Planta Piloto de Ingeniería Química. Universidad Nacional del Sur. Planta Piloto de Ingeniería Química; ArgentinaFil: Vazquez, Gustavo Esteban. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad Católica del Uruguay; UruguayFil: Páez, Juan A.. Consejo Superior de Investigaciones Científicas. Instituto de Química Médica; EspañaFil: Diaz, Monica Fatima. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Planta Piloto de Ingeniería Química. Universidad Nacional del Sur. Planta Piloto de Ingeniería Química; Argentina. Universidad Nacional del Sur. Departamento de Ingeniería Química; ArgentinaFil: Campillo Martín, Nuria Eugenia. Consejo Superior de Investigaciones Científicas. Centro de Investigaciones Biológicas; Españ

Método y aparato para la detección de sustancias o analitos a partir del análisis de una o varias muestras

Referencia OEPM: P200301292.-- Fecha de solicitud: 30/05/2003.-- Titulares: Instituto Nacional de Técnica Aeroespacial “Esteban Terradas”, Sener ingeniería y Sistemas S.A. y Consejo Superior de Investigaciones Científicas (CSIC).El método comprende mezclar la muestra con un líquido tampón apropiado, homogeneizar dicha muestra, añadir reactivos a la misma, filtrarla, inyectar la muestra a una cámara de incubación, dejar reaccionar la muestra con un biosensor, lavar el exceso de muestra no reaccionada y detectar la muestra retenida en el biosensor. El aparato incluye un módulo homogeneizador de muestras con un dispositivo piezoeléctrico de ultrasonidos formado por un convertidor y una bocina; un módulo de procesamiento de muestras, que incluye un recipiente de homogeneización y un bastidor móvil; un módulo de gestión de reactivos y soluciones, que incluye una jeringa motorizada, un módulo de reacción, compuesto por un soporte que forma una cámara de reacción, y un módulo de lectura de datos que incluye un diodo láser y una cámara CCD.Peer reviewe

High-Precision Photothermal Ablation using Biocompatible Palladium Nanoparticles and Laser Scanning Microscopy

Herein, we report a straightforward method for the scalable preparation of Pd nanoparticles (Pd-NPs) with reduced inherent cytotoxicity and high photothermal conversion capacity. These Pd-NPs are rapidly taken up by cells and able to kill labeled cancer cells upon short exposure to near-infrared (NIR) light. Following cell treatment with Pd-NPs, ablated areas were patterned with high precision by laser scanning microscopy, allowing one to perform cell migration assays with unprecedented accuracy. Using coherent Raman microscopy, cells containing Pd-NPs were simultaneously ablated and imaged. This novel methodology was combined with intravital imaging to mediate microablation of cancerous tissue in tumor xenografts in mice

Vertical Configuration of a Side Scan Sonar for the Monitoring of Posidonia oceanica Meadows

[EN] Posidonia oceanica meadows are ecosystem engineers that play several roles in marine environment maintenance. In this sense, monitoring of the spatial distribution and health status of their meadows is key to make decisions about protecting them against their degradation. With the aim of checking the ability of a simple low-cost acoustic method to acquire information about the state of P. oceanica meadows as ecosystem indicators, ground-truthing and acoustic data were acquired over several of these meadows on the Levantine coast of Spain. A 200 kHz side scan sonar in a vertical configuration was used to automatically estimate shoot density, canopy height and cover of the meadows. The wide athwartship angle of the transducer together with its low cost and user friendliness entail the main advantages of this system and configuration: both improved beam path and detection invariance against boat rolling. The results show that canopy height can be measured acoustically. Furthermore, the accumulated intensity of the echoes from P. oceanica in the first 30 centimeters above the bottom is indirectly related to shoot density and cover, showing a relation that should be studied deeply.Funding for open access charge: Universitat Politècnica de ValènciaLlorens-Escrich, S.; Tamarit, E.; Hernandis, S.; Sánchez-Carnero, N.; Rodilla, M.; Pérez Arjona, I.; Moszynski, M.... (2021). Vertical Configuration of a Side Scan Sonar for the Monitoring of Posidonia oceanica Meadows. Journal of Marine Science and Engineering. 9(12):1-15. https://doi.org/10.3390/jmse912133211591