The Versatile Dioctadecyldimethylammonium Bromide

Dioctadecyldimethylammonium bromide (DODAB) is a quaternary ammonium surfactant (Quat) with interesting properties and applications. In this chapter, DODAB characteristics as compared to other Quats emphasize its self-assembly in aqueous solutions and the novel applications involving this useful cationic lipid so easily combined with biomolecules and interfaces to yield a wide range of novel uses in many fields such as delivery of drugs, vaccines and genes, design of nanoparticles, modification of interfaces, and many others yet to come

Characterization of Toxoplasma gondii subtelomeric-like regions: identification of a long-range compositional bias that is also associated with gene-poor regions

Background Chromosome ends are composed of telomeric repeats and subtelomeric regions, which are patchworks of genes interspersed with repeated elements. Although chromosome ends display similar arrangements in different species, their sequences are highly divergent. In addition, these regions display a particular nucleosomal composition and bind specific factors, therefore producing a special kind of heterochromatin. Using data from currently available draft genomes we have characterized these putative Telomeric Associated Sequences in Toxoplasma gondii. Results An all-vs-all pairwise comparison of T. gondii assembled chromosomes revealed the presence of conserved regions of ∼ 30 Kb located near the ends of 9 of the 14 chromosomes of the genome of the ME49 strain. Sequence similarity among these regions is ∼ 70%, and they are also highly conserved in the GT1 and VEG strains. However, they are unique to Toxoplasma with no detectable similarity in other Apicomplexan parasites. The internal structure of these sequences consists of 3 repetitive regions separated by high-complexity sequences without annotated genes, except for a gene from the Toxoplasma Specific Family. ChIP-qPCR experiments showed that nucleosomes associated to these sequences are enriched in histone H4 monomethylated at K20 (H4K20me1), and the histone variant H2A.X, suggesting that they are silenced sequences (heterochromatin). A detailed characterization of the base composition of these sequences, led us to identify a strong long-range compositional bias, which was similar to that observed in other genomic silenced fragments such as those containing centromeric sequences, and was negatively correlated to gene density. Conclusions We identified and characterized a region present in most Toxoplasma assembled chromosomes. Based on their location, sequence features, and nucleosomal markers we propose that these might be part of subtelomeric regions of T. gondii. The identified regions display a unique trinucleotide compositional bias, which is shared (despite the lack of any detectable sequence similarity) with other silenced sequences, such as those making up the chromosome centromeres. We also identified other genomic regions with this compositional bias (but no detectable sequence similarity) that might be functionally similar.Fil: Dalmasso, Maria Carolina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - La Plata. Instituto de Investigaciones Biotecnológicas. Instituto de Investigaciones Biotecnológicas "Dr. Raúl Alfonsín" (sede Chascomús). Universidad Nacional de San Martín. Instituto de Investigaciones Biotecnológicas. Instituto de Investigaciones Biotecnológicas "Dr. Raúl Alfonsín" (sede Chascomús); ArgentinaFil: Carmona, Santiago Javier. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - La Plata. Instituto de Investigaciones Biotecnológicas. Instituto de Investigaciones Biotecnológicas "Dr. Raúl Alfonsín" (sede Chascomús). Universidad Nacional de San Martín. Instituto de Investigaciones Biotecnológicas. Instituto de Investigaciones Biotecnológicas "Dr. Raúl Alfonsín" (sede Chascomús); ArgentinaFil: Ángel, Sergio Oscar. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - La Plata. Instituto de Investigaciones Biotecnológicas. Universidad Nacional de San Martín. Instituto de Investigaciones Biotecnológicas; ArgentinaFil: Agüero, Fernan Gonzalo. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - La Plata. Instituto de Investigaciones Biotecnológicas. Universidad Nacional de San Martín. Instituto de Investigaciones Biotecnológicas; Argentin

A template based approach for human action recognition

Visual analysis of human movements concerns the understanding of human activities from image sequences. The goal of the action/gesture recognition is to recognize the label that corresponds to an action or gesture made by a human in a sequence of images. To solve this problem, the researchers have proposed solutions that range from object recognition techniques, to speech recognition techniques, face recognition or brain function . The techniques presented in this thesis, are related to a set of techniques that condense a video sequence into a template that retain important information to action/gestures classification applying standard object recognition techniques. In a first stage of this thesis, we have proposed a view-based temporal template approach for action/gesture representation from tensors. The templates are computed from three different projections considering a video sequence as a third-order tensor. We compute each projection from the fibers of the tensor using a combination of simple functions . We have studied which function and feature extractor/descriptor is the most suitable to project the template from the tensor. We have tested five different simple functions used to project the fibers, namely, supremum, mean, standard deviation, skewness and kurtosis using public datasets. We have also studied the performance obtained applying four feature extractors/descriptors like PHOW, LIOP, HOG and SMFs. Using more complex datasets, we have assessed the most suitable feature representation for our templates (Bag Of Words or Fisher Vectors) and the complementarity among the features computed from each simple function (Max, Mean, Standard Deviation, Kurtosis y Skewness). Finally, we have studied the comptementarity with a successful technique like Improved Dense Trajectories. The experiments have shown that Standard Deviation function and PHOW extractor/descriptor are the most suitable for our templates. The results have shown also that our 3 projection templates overcome most state-of-the-art techniques in more complex datasets when we combine the templates with Fisher Vector representation . The features extracted by each simple function are complementary among them and that added to HOG, HOF and MBH improves the performance of IDTs. Derived from this thesis, we have also presented another view-based temporal temptate approach for action recognition obtained from a Radon transform projection and that allows the temporal segmentation of human actions in real time. First, we propose a generalization of the R transform that it is useful to adapt the transform to the problem to be solve. We have studied the performance in three functions, namely, Max, Mean and Standard Deviation for pre-segmentad human action recognition using a public dataset, and we have compared the results against traditional R transform . The results have shown that Maxfunction obtains the best performance when it is applied on Radon transform and that our technique overcomes many state-of-the-art techniques in action recognition. In a second stage, we have modified the classifier to adapt it to temporal segmentation of human actions. To assess the performance, we have merged Weizman and Hollywood actions datasets and we have measured the performance of the method to identify isolated actions. The experiments have shown that our technique overcomes the state-of-the-art techniques in Weizman dataset in no pre-segmented human actions.El análisis visual de movimientos humanos hace referencia al entendimiento de la actividad humana en secuencias de video. El objetivo del reconocimiento de acciones/gestos en ámbito de la Visión por Computador, es identificar el nombre que corresponde a una acción o gesto realizado en una secuencia de imágenes. Para dar solución a este problema, los investigadores han propuesto soluciones que van desde la aplicación de técnicas que derivan del reconocimiento de objetos, del reconocimiento del habla, del reconocimiento facial o del funcionamiento del cerebro. Las técnicas presentadas en esta tesis, están relacionadas con un conjunto de técnicas que intentan condensar una secuencia de video en unas templates que retienen información importante de cara a la discriminación entre acciones/gestos aplicando técnicas estándar de reconocimiento de objetos. En la primera parte de esta tesis, hemos propuesto una aproximación basada en template para la representación de acciones/gestos a partir de tensores. Nuestras templates se calculan desde tres proyecciones diferentes considerando una secuencia de vídeo como un tensor de tercer orden. Calculamos cada proyección desde las fibras del tensor de tercer orden utilizando funciones simples. Hemos hecho un estudio exhaustivo para encontrar qué función debe ser utilizada para proyectar el template desde el tensor, y qué extractor/descriptor es el más adecuado. Utilizando datasets públicos simples, hemos testeado cinco funciones diferentes simples para proyectar las fibras, llamadas, Max, Mean, Standard Deviation, Kurtosis y Skewness. Hemos estudiado también el rendimiento obtenido aplicando a nuestras templates, cuatro técnicas de extracción/descripción de características del estado del arte como PHOW, LIOP, HOG y SMFs. Utilizando datasets más complejos, hemos estudiado cuál es la mejor representación de las características extraídas de las templates (Bag Of Words o Fisher Vectores), y la complementariedad entre las características extraídas con cada una de las cinco funciones (Max, Mean, Standard Deviation, Kurtosis y Skewness) y la complementariedad de estas con una exitosa técnica como Improved Dense Trajectories. Los experimentos han demostrado que la desviación estándar es la mejor función para proyectar las fibras en las templates, y que PHOW obtiene el mejor rendimiento como detector/descriptor en las templates obtenidas. Los datasets más complejos han mostrado que la mejor representación para las características extraídas de las templates es Fisher Vectores, que existe complementariedad entre las características extraídas con cada una de las funciones y que la fusión de estas características con Improved Dense Trajectories, hace que este último mejore su rendimiento. Derivado de los trabajos de esta tesis, también presentamos otra aproximación basada en template por el reconocimiento de acciones/gestos que se obtiene de una proyección derivada de la transformada de Radon y que permite la segmentación temporal de acciones en tiempo real. Primero hemos planteado una generalización de la transformada R que permite adaptar la transformada al problema a resolver mediante la función de proyección. Hemos estudiado su rendimiento para las funciones Max, Mean y Standard Deviation en reconocimiento de acciones pre-segmentadas sobre un dataset público y comparado los resultados con la transformada R. Los resultados han mostrado que la función Max obtiene el mejor resultado cuando se aplica sobre la transformada de Radon y que nuestra técnica supera a muchos métodos del estado del arte en reconocimiento de acciones. En una segunda fase, hemos introducido una modificación en la etapa de clasificación de nuestra técnica para permitir segmentar acciones temporalmente. Para evaluar su rendimiento, hemos concatenado acciones de los datasets Weizmann y Hollywood y medido la capacidad de la técnica para identificar cada una de las acciones individuales. Los experimentos han demostrado que nuestra técnica rinde mejor en la segmentación de acciones del Weizmann dataset que las técnicas del estado del arteL’anàlisi visual de moviments humans fa referència al enteniment d’activitat humana en seqüències de vídeo. L’objectiu del reconeixement d’accions/gestos en l’àmbit de la Visió per Computador, és identificar el nom que correspon a una acció o gest realitzat en una seqüència d’imatges. Per donar solució a aquest problema, els investigadors han proposat solucions que van des de l’aplicació de tècniques que deriven del reconeixement d’objectes, del reconeixement de la parla, del reconeixement facial o del funcionament del cervell. Les tècniques presentades en aquesta tesi, estan relacionades amb un conjunt de tècniques que intenten condensar una seqüència de vídeo en uns templates que retinguin informació important de cara a la discriminació entre accions/gestos aplicant tècniques estàndards de reconeixement d’objectes. A la primera part d’aquesta tesi, hem proposat una aproximació basada en template per la representació d’accions/gestos a partir de tensors. Les nostres templates es calculen des de tres projeccions diferents considerant una seqüència de vídeo com un tensor de tercer ordre. Calculem cada projecció des de les fibres del tensor de tercer ordre utilitzant funcions simples. Hem fet un estudi exhaustiu per trobar quina funció ha de ser utilitzada per projectar el template des del tensor, i quin extractor/descriptor és el més adequat. Utilitzant datasets públics simples, hem testejat cinc funcions diferents simples per projectar les fibres, anomenades, Max, Mean, Standard Deviation, Kurtosi i Skewness. Hem estudiat també el rendiment obtingut aplicant a les nostres templates, quatre tècniques d’extracció/descripció de característiques de l’estat de l’art com PHOW, LIOP, HOG i SMFs. Utilitzant datasets més complexes, hem estudiat quina és la millor representació de les característiques extretes de les templates (Bag Of Words o Fisher Vectors) i la complementarietat entre les característiques extretes amb cada una de les cinc funcions (Max, Mean, Standard Deviation, Kurtosi i Skewness) i la complementarietat d’aquestes amb una exitosa tècnica com Improved Dense Trajectories. Els experiments han demostrat que la desviació estàndard és la millor funció per projectar les fibres en les templates, i que PHOW obté el millor rendiment com a detector/descriptor en les templates obtingudes. Els datasets més complexes han mostrat que la millor representació per a les característiques extretes de les templates és amb Fisher Vectors, que existeix complementarietat entre les característiques extretes amb cada una de les funcions i que la fusió d’aquestes característiques amb Improved Dense Trajectories, fa que aquest últim millori el seu rendiment. Derivat dels treballs d’aquesta tesi, també presentem una altre aproximació basada en template pel reconeixement d’accions/gestos que s’obté d’una projecció derivada de la transformada de Radon i que permet la segmentació temporal d’accions en temps real. Primer hem plantejat una generalització de la transformada R que permet adaptar la transformada al problema a resoldre mitjançant la funció de projecció. Hem estudiat el seu rendiment per a les funcions Max, Mean i Standard Deviation en reconeixement d’accions pre-segmentades sobre un dataset públic i comparat els resultats amb la transformada R. Els resultats han mostrat que la funció Max obté el millor resultat quan s’aplica sobre la transformada de Radon i que la nostra tècnica supera a molts mètodes de l’estat de l’art en reconeixement d’accions. A una segona fase, hem introduït una modificació a la etapa de classificació de la nostra tècnica per permetre segmentar accions temporalment. Per avaluar el seu rendiment, hem concatenat accions dels datasets Weizmann i Hollywood i mesurat la capacitat de la tècnica per identificar cadascuna de les accions individuals. Els experiments han demostrat que la nostra tècnica rendeix millor en la segmentació de les accions del dataset Weizmann que les tècniques de l’estat de l’art.Postprint (published version

Biomimetic Nanomaterials from the Assembly of Polymers, Lipids, and Surfactants

Nanostructured materials require evaluation at a molecular level to become controllable and useful in drug and vaccine delivery. Over the years self-assembled nanomaterials such as nanoparticles and thin films have been prepared, characterized and used for biomedical applications. In this review meaningful examples of biomimetic nanomaterials and their construction based on intermolecular interactions such as the electrostatic attraction or the hydrophobic effect will be discussed. Emphasis will be placed on the interactions between polymers, lipids, surfactants and surfaces leading to bioactive supramolecular assemblies such as nanoparticles and coatings. Among the important applications of the self-assembled nanostructures and films to be reviewed are their antimicrobial effect and their adjuvant activity for vaccine delivery

Biomimetic nanoparticles: preparation, characterization and biomedical applications

Mimicking nature is a powerful approach for developing novel lipid-based devices for drug and vaccine delivery. In this review, biomimetic assemblies based on natural or synthetic lipids by themselves or associated to silica, latex or drug particles will be discussed. In water, self-assembly of lipid molecules into supramolecular structures is fairly well understood. However, their self-assembly on a solid surface or at an interface remains poorly understood. In certain cases, hydrophobic drug granules can be dispersed in aqueous solution via lipid adsorption surrounding the drug particles as nanocapsules. In other instances, hydrophobic drug molecules attach as monomers to borders of lipid bilayer fragments providing drug formulations that are effective in vivo at low drug-to-lipid-molar ratio. Cationic biomimetic particles offer suitable interfacial environment for adsorption, presentation and targeting of biomolecules in vivo. Thereby antigens can effectively be presented by tailored biomimetic particles for development of vaccines over a range of defined and controllable particle sizes. Biomolecular recognition between receptor and ligand can be reconstituted by means of receptor immobilization into supported lipidic bilayers allowing isolation and characterization of signal transduction steps

Compressive Imaging Using RIP-Compliant CMOS Imager Architecture and Landweber Reconstruction

In this paper, we present a new image sensor architecture for fast and accurate compressive sensing (CS) of natural images. Measurement matrices usually employed in CS CMOS image sensors are recursive pseudo-random binary matrices. We have proved that the restricted isometry property of these matrices is limited by a low sparsity constant. The quality of these matrices is also affected by the non-idealities of pseudo-random number generators (PRNG). To overcome these limitations, we propose a hardware-friendly pseudo-random ternary measurement matrix generated on-chip by means of class III elementary cellular automata (ECA). These ECA present a chaotic behavior that emulates random CS measurement matrices better than other PRNG. We have combined this new architecture with a block-based CS smoothed-projected Landweber reconstruction algorithm. By means of single value decomposition, we have adapted this algorithm to perform fast and precise reconstruction while operating with binary and ternary matrices. Simulations are provided to qualify the approach.Ministerio de Economía y Competitividad TEC2015-66878-C3-1-RJunta de Andalucía TIC 2338-2013Office of Naval Research (USA) N000141410355European Union H2020 76586

Key features of a succesful invasive macroalgae: the case of asparagopsis taxiformis in Alboran Sea

Asparagopsis taxiformis (Bonnemaisoniales, Rhodophyta) is considered one of the most invasive seaweeds in the Mediterranean, and is included in the spanish checklist of invasive species. Recorded for first time in Southern Spain nearly twenty years ago, we are now ready to highlight its key features to have become a successful invader in Alboran Sea. Genetic studies showed that only one lineage of this species complex, is invasive in Alboran Sea, the lineage 2, which exhibits a wide physiological plasticity, exhibited in a wide thermal adaptation of performances of photosynthetic parameters like Pmax and α. Furthermore, the species is able to inhabit from shallow subtidal up to depths over -30m, due to its low Ic. The species exhibits a trigenetic life-cycle, with an invasive gametophyte dominating the host community, and a free-living tetrasporophyte (Falkenbergia phase) being the dispersal one. The gametophyte is present all the year round, and exhibits a high recruitment and vegetative growth capacity, which support more than 90% of the community biomass. Furthermore, sexual reproduction was perfomed during the whole year, except in winter months, accounting in summer months with more than 50% of the population with reproductive structures. Minimum size for reproduction was low (4-6 cm), considering the maximal size observed for the species in the study site (30 cm). Statistical anaylisis has shown no relationship of reproduction with environmental factors, such as nutrients or temperatura. These features, together with some other more, become A. taxiformis in an invasive species already well settled in Alboran Sea.Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech