Deep learning neural networks in malaria diagnosis

Malaria is a serious disease mostly spread in tropical and subtropical areas that causes 438.000 deaths per year. Current malaria diagnosis relies primarily on microscopic examination of stained blood films. This method is time consuming and prone to human error, even in experienced hands. Thus, there is a need for the development of an automatic technique that is able to detect malaria in a sensitive and unsupervised manner. Deep learning networks are a novel field that promises to have a key role in this automatic detection. In this thesis, we propose a system that collects much of the research conducted about this issue and that proposes new schemes to enhance the performance. In particular, a solution based on convolutional neural networks has shown a clear improvement of the results in the detection of malaria

Human Albumin Impairs Amyloid β-peptide Fibrillation Through its C-terminus: From docking Modeling to Protection Against Neurotoxicity in Alzheimer's disease

Alzheimer's disease (AD) is a neurodegenerative process characterized by the accumulation of extracellular deposits of amyloid β-peptide (Aβ), which induces neuronal death. Monomeric Aβ is not toxic but tends to aggregate into β-sheets that are neurotoxic. Therefore to prevent or delay AD onset and progression one of the main therapeutic approaches would be to impair Aβ assembly into oligomers and fibrils and to promote disaggregation of the preformed aggregate. Albumin is the most abundant protein in the cerebrospinal fluid and it was reported to bind Aβ impeding its aggregation. In a previous work we identified a 35-residue sequence of clusterin, a well-known protein that binds Aβ, that is highly similar to the C-terminus (CTerm) of albumin. In this work, the docking experiments show that the average binding free energy of the CTerm-Aβ1–42 simulations was significantly lower than that of the clusterin-Aβ1–42 binding, highlighting the possibility that the CTerm retains albumin's binding properties. To validate this observation, we performed in vitro structural analysis of soluble and aggregated 1 μM Aβ1–42 incubated with 5 μM CTerm, equimolar to the albumin concentration in the CSF. Reversed-phase chromatography and electron microscopy analysis demonstrated a reduction of Aβ1–42 aggregates when the CTerm was present. Furthermore, we treated a human neuroblastoma cell line with soluble and aggregated Aβ1–42 incubated with CTerm obtaining a significant protection against Aβ-induced neurotoxicity. These in silico and in vitro data suggest that the albumin CTerm is able to impair Aβ aggregation and to promote disassemble of Aβ aggregates protecting neurons

Implantación de un barómetro de talento mediante tecnologías Big Data

[ANGLÈS] Barometer of talent whose goal is to measure and evaluate the talent of Barcelona. It has been developed using Big Data technologies, particullarly, a Hadoop based solution.[CASTELLÀ] Barómetro de talento cuyo objectivo es medir y evaluar el talento de Barcelona. Su desarrollo se ha llevado a cabo mediante tecnologías Big Data, en particular, una solución basada en Hadoop.[CATALÀ] Baròmetre de talent que pretén mesurar i avaluar el talent a la ciutat de Barcelona. El seu desenvolupament s'ha dut a terme amb tecnologies Big Data, concretament amb una solució basada en Hadoop

Implantación de un barómetro de talento mediante tecnologías Big Data

[ANGLÈS] Barometer of talent whose goal is to measure and evaluate the talent of Barcelona. It has been developed using Big Data technologies, particullarly, a Hadoop based solution.[CASTELLÀ] Barómetro de talento cuyo objectivo es medir y evaluar el talento de Barcelona. Su desarrollo se ha llevado a cabo mediante tecnologías Big Data, en particular, una solución basada en Hadoop.[CATALÀ] Baròmetre de talent que pretén mesurar i avaluar el talent a la ciutat de Barcelona. El seu desenvolupament s'ha dut a terme amb tecnologies Big Data, concretament amb una solució basada en Hadoop

Implantación de un barómetro de talento mediante tecnologías Big Data

[ANGLÈS] Barometer of talent whose goal is to measure and evaluate the talent of Barcelona. It has been developed using Big Data technologies, particullarly, a Hadoop based solution.[CASTELLÀ] Barómetro de talento cuyo objectivo es medir y evaluar el talento de Barcelona. Su desarrollo se ha llevado a cabo mediante tecnologías Big Data, en particular, una solución basada en Hadoop.[CATALÀ] Baròmetre de talent que pretén mesurar i avaluar el talent a la ciutat de Barcelona. El seu desenvolupament s'ha dut a terme amb tecnologies Big Data, concretament amb una solució basada en Hadoop

Human Albumin Impairs Amyloid β-peptide Fibrillation Through its C-terminus: From docking Modeling to Protection Against Neurotoxicity in Alzheimer's disease

Alzheimer's disease (AD) is a neurodegenerative process characterized by the accumulation of extracellular deposits of amyloid β-peptide (Aβ), which induces neuronal death. Monomeric Aβ is not toxic but tends to aggregate into β-sheets that are neurotoxic. Therefore to prevent or delay AD onset and progression one of the main therapeutic approaches would be to impair Aβ assembly into oligomers and fibrils and to promote disaggregation of the preformed aggregate. Albumin is the most abundant protein in the cerebrospinal fluid and it was reported to bind Aβ impeding its aggregation. In a previous work we identified a 35-residue sequence of clusterin, a well-known protein that binds Aβ, that is highly similar to the C-terminus (CTerm) of albumin. In this work, the docking experiments show that the average binding free energy of the CTerm-Aβ1–42 simulations was significantly lower than that of the clusterin-Aβ1–42 binding, highlighting the possibility that the CTerm retains albumin's binding properties. To validate this observation, we performed in vitro structural analysis of soluble and aggregated 1 μM Aβ1–42 incubated with 5 μM CTerm, equimolar to the albumin concentration in the CSF. Reversed-phase chromatography and electron microscopy analysis demonstrated a reduction of Aβ1–42 aggregates when the CTerm was present. Furthermore, we treated a human neuroblastoma cell line with soluble and aggregated Aβ1–42 incubated with CTerm obtaining a significant protection against Aβ-induced neurotoxicity. These in silico and in vitro data suggest that the albumin CTerm is able to impair Aβ aggregation and to promote disassemble of Aβ aggregates protecting neurons

The antigen-binding fragment of human gamma immunoglobulin prevents amyloid β-peptide folding into β-sheet to form oligomers

The amyloid beta-peptide (Aβ) plays a leading role in Alzheimer's disease (AD) physiopathology. Even though monomeric forms of Aβ are harmless to cells, Aβ can aggregate into β-sheet oligomers and fibrils, which are both neurotoxic. Therefore, one of the main therapeutic approaches to cure or delay AD onset and progression is targeting Aβ aggregation. In the present study, we show that a pool of human gamma immunoglobulins (IgG) protected cortical neurons from the challenge with Aβ oligomers, as assayed by MTT reduction, caspase-3 activation and cytoskeleton integrity. In addition, we report the inhibitory effect of IgG on Aβ aggregation, as shown by Thioflavin T assay, size exclusion chromatography and atomic force microscopy. Similar results were obtained with Palivizumab, a human anti-sincitial virus antibody. In order to dissect the important domains, we cleaved the pool of human IgG with papain to obtain Fab and Fc fragments. Using these cleaved fragments, we functionally identified Fab as the immunoglobulin fragment inhibiting Aβ aggregation, a result that was further confirmed by an in silico structural model. Interestingly, bioinformatic tools show a highly conserved structure able to bind amyloid in the Fab region. Overall, our data strongly support the inhibitory effect of human IgG on Aβ aggregation and its neuroprotective role.This work was supported by the Plan Estatal de I+D+I 2013-2016 and the ISCIII-Subdirección General de Evaluación y Fomento de la Investigación (Grants PI13/00408, PI13/00135, and Miguel Servet Grant CP10/00548 to X.A.) and FEDER Funds; SAF2014-52228-R; BIO2014-57518-R and Fundació La Marató-TV3 (Nº 20140210; Nº 20134030