Search results for: Miguel A. Gomez

Authors: Iñaki Iturria, Pasquale Russo, Montserrat Nacher-Vázquez, Giuseppe Spano, Paloma López, Miguel Angel Pardo

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Introduction: It is known that some Lactic Acid Bacteria (LAB) present an interesting probiotic effect. Probiotic bacteria stimulate host resistance to microbial pathogens and thereby aid in immune response, and modulate the host's immune responses to antigens with a potential to down-regulate hypersensitivity reactions. Therefore, probiotic therapy is valuable against intestinal infections and may be beneficial in the treatment of Inflammatory Bowel Disease (IBD). Several in vitro tests are available to evaluate the probiotic potential of a LAB strain. However, an in vivo model is required to understand the interaction between the host immune system and the bacteria. During the last few years, zebrafish (Danio rerio) has gained interest as a promising vertebrate model in this field. This organism has been extensively used to study the interaction between the host and the microbiota, as well as the host immune response under several microbial infections. In this work, we report on the use of the zebrafish model to investigate in vivo the colonizing ability and the immunomodulatory effect of probiotic LAB. Methods: Lactobacillus strains belonging to different LAB species were fluorescently tagged and used to colonize germ-free zebrafish larvae gastrointestinal tract (GIT). Some of the strains had a well-documented probiotic effect (L. acidophilus LA5); while others presented an exopolysaccharide (EPS) producing phenotype, thus allowing evaluating the influence of EPS in the colonization and immunomodulatory effect. Bacteria colonization was monitored for 72 h by direct observation in real time using fluorescent microscopy. CFU count per larva was also evaluated at different times. The immunomodulatory effect was assessed analysing the differential expression of several innate immune system genes (MyD88, NF-κB, Tlr4, Il1β and Il10) by qRT- PCR. The anti-inflammatory effect was evaluated using a chemical enterocolitis zebrafish model. The protective effect against a pathogen was also studied. To that end, a challenge test was developed using a fluorescently tagged pathogen (Vibrio anguillarum-GFP+). The progression of the infection was monitored up to 3 days using a fluorescent stereomicroscope. Mortality rates and CFU counts were also registered. Results and conclusions: Larvae exposed to EPS-producing bacteria showed a higher fluorescence and CFU count than those colonized with no-EPS phenotype LAB. In the same way, qRT-PCR results revealed an immunomodulatory effect on the host after the administration of the strains with probiotic activity. A downregulation of proinflammatory cytoquines as well as other cellular mediators of inflammation was observed. The anti-inflammatory effect was found to be particularly marked following exposure to LA% strain, as well as EPS producing strains. Furthermore, the challenge test revealed a protective effect of probiotic administration. As a matter of fact, larvae fed with probiotics showed a decrease in the mortality rate ranging from 20 to 35%. Discussion: In this work, we developed a promising model, based on the use of gnotobiotic zebrafish coupled with a bacterial fluorescent tagging in order to evaluate the probiotic potential of different LAB strains. We have successfully used this system to monitor in real time the colonization and persistence of exogenous LAB within the gut of zebrafish larvae, to evaluate their immunomodulatory effect and for in vivo competition assays. This approach could bring further insights into the complex microbial-host interactions at intestinal level.

Keywords: gnotobiotic, immune system, lactic acid bacteria, probiotics, zebrafish

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Authors: S. Delgado, C. Cerrada, R. S. Gómez

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This research introduces an approach to voxelizing the surfaces of triangular meshes with efficiency and accuracy. Our method leverages parallel equidistant scan-lines and introduces a Gap Detection technique to address the limitations of existing approaches. We present a comprehensive study showcasing the method's effectiveness, scalability, and versatility in different scenarios. Voxelization is a fundamental process in computer graphics and simulations, playing a pivotal role in applications ranging from scientific visualization to virtual reality. Our algorithm focuses on enhancing the voxelization process, especially for complex models and high resolutions. One of the major challenges in voxelization in the Graphics Processing Unit (GPU) is the high cost of discovering the same voxels multiple times. These repeated voxels incur in costly memory operations with no useful information. Our scan-line-based method ensures that each voxel is detected exactly once when processing the triangle, enhancing performance without compromising the quality of the voxelization. The heart of our approach lies in the use of parallel, equidistant scan-lines to traverse the interiors of triangles. This minimizes redundant memory operations and avoids revisiting the same voxels, resulting in a significant performance boost. Moreover, our method's computational efficiency is complemented by its simplicity and portability. Written as a single compute shader in Graphics Library Shader Language (GLSL), it is highly adaptable to various rendering pipelines and hardware configurations. To validate our method, we conducted extensive experiments on a diverse set of models from the Stanford repository. Our results demonstrate not only the algorithm's efficiency, but also its ability to produce 26 tunnel free accurate voxelizations. The Gap Detection technique successfully identifies and addresses gaps, ensuring consistent and visually pleasing voxelized surfaces. Furthermore, we introduce the Slope Consistency Value metric, quantifying the alignment of each triangle with its primary axis. This metric provides insights into the impact of triangle orientation on scan-line based voxelization methods. It also aids in understanding how the Gap Detection technique effectively improves results by targeting specific areas where simple scan-line-based methods might fail. Our research contributes to the field of voxelization by offering a robust and efficient approach that overcomes the limitations of existing methods. The Gap Detection technique fills a critical gap in the voxelization process. By addressing these gaps, our algorithm enhances the visual quality and accuracy of voxelized models, making it valuable for a wide range of applications. In conclusion, "Closing the Gap: Efficient Voxelization with Equidistant Scan-lines and Gap Detection" presents an effective solution to the challenges of voxelization. Our research combines computational efficiency, accuracy, and innovative techniques to elevate the quality of voxelized surfaces. With its adaptable nature and valuable innovations, this technique could have a positive influence on computer graphics and visualization.

Keywords: voxelization, GPU acceleration, computer graphics, compute shaders

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Authors: Miguel García-Ferrús, Yolanda Domínguez, M Angeles Castillo, M Antonia Ferrús, Ana Jiménez-Belenguer

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Antibiotic resistance is a growing public health concern worldwide, and it is now regarded as a critical issue within the "One Health" approach that affects human and animal health, agriculture, and environmental waste management. This concept focuses on the interconnected nature of human, animal and environmental health, and WHO highlights zoonotic diseases, food safety, and antimicrobial resistance as three particularly relevant areas for this framework. Fresh vegetables are garnering attention in the food chain due to the presence of pathogens and because they can act as a reservoir for Antibiotic Resistance Bacteria (ARB) and Antibiotic Resistance Genes (ARG). These fresh products are frequently consumed raw, thereby contributing to the spread and transmission of antibiotic resistance. Therefore, the aim of this research was to study the microbiological quality, the prevalence of ARB, and their role in the dissemination of ARG in fresh vegetables intended for human consumption. For this purpose, 102 samples of fresh vegetables (30 lettuce, 30 cabbage, 18 strawberries and 24 spinach) from different retail establishments in Valencia (Spain) have been analyzed to determine their microbiological quality and their role in spreading ARB and ARG. The samples were collected and examined according to standardized methods for total viable bacteria, coliforms, Shiga toxin-producing Escherichia coli (STEC), Listeria monocytogenes and Salmonella spp. Isolation was made in culture media supplemented with antibiotics (cefotaxime and meropenem). A total of 239 strains resistant to beta-lactam antibiotics (Third-Generation Cephalosporins and Carbapenems) were isolated. Thirty Gram-negative isolates were selected and biochemically identified or partial sequencing of 16S rDNA. Their sensitivity to 12 antibiotic discs was determined using the Kirby-Bauer disc diffusion technique to different therapeutic groups. To determine the presence of ARG, PCR assays for the direct sample and selected isolate DNA were performed for main expanded spectrum beta-lactamase (ESBL)-, carbapenemase-encoding genes and plasmid-mediated quinolone resistance genes. From the total samples, 68% (24/24 spinach, 28/30 lettuce and 17/30 cabbage) showed total viable bacteria levels over the accepted standard 10(2)-10(5) cfu/g range; and 48% (24/24 spinach, 19/30 lettuce and 6/30) showed coliforms levels over the accepted standard 10(2)-10(4) cfu/g range. In 9 samples (3/24 spinach, 3/30 lettuce, 3/30 cabbage; 9/102 (9%)) E. coli levels were higher than the standard 10(3) cfu/g limit. Listeria monocytogenes, Salmonella and STEC have not been detected. Six different bacteria species were isolated from samples. Stenotrophomonas maltophilia (64%) was the prevalent species, followed by Acinetobacter pitii (14%) and Burkholderia cepacia (7%). All the isolates were resistant to at least one tested antibiotic, including meropenem (85%) and ceftazidime (46%). Of the total isolates, 86% were multidrug-resistant and 68% were ESBL productors. Results of PCR showed the presence of resistance genes to beta-lactams blaTEM (4%) and blaCMY-2 (4%), to carbapenemes blaOXA-48 (25%), blaVIM (7%), blaIMP (21%) and blaKPC (32%), and to quinolones QnrA (7%), QnrB (11%) and QnrS (18%). Thus, fresh vegetables harboring ARB and ARG constitute a potential risk to consumers. Further studies must be done to detect ARG and how they propagate in non-medical environments.

Keywords: ESBL, β-lactams, resistances, fresh vegetables.

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Authors: Camilo Cerda Sarabia, Fernanda Bravo Cornejo, Diego Santibanez Oyarce, Hugo Osses Prado, Esteban Gómez Terán, Belén Diaz Diaz, Raúl Caulier-Cisterna, Jorge Vergara-Quezada, Ana Moya-Beltrán

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Antimicrobial resistance (AMR) represents a significant and rapidly escalating global health threat. Projections estimate that by 2050, AMR infections could claim up to 10 million lives annually. Respiratory infections, in particular, pose a severe risk not only to individual patients but also to the broader public health system. Despite the alarming rise in resistant respiratory infections, AMR within the lung microbiome (microbial community) remains underexplored and poorly characterized. The lungs, as a complex and dynamic microbial environment, host diverse communities of microorganisms whose interactions and resistance mechanisms are not fully understood. Unlike studies that focus on individual genomes, analyzing the entire microbiome provides a comprehensive perspective on microbial interactions, resistance gene transfer, and community dynamics, which are crucial for understanding AMR. However, this holistic approach introduces significant computational challenges and exposes the limitations of traditional analytical methods such as the difficulty of identifying the AMR. Machine learning has emerged as a powerful tool to overcome these challenges, offering the ability to analyze complex genomic data and uncover novel insights into AMR that might be overlooked by conventional approaches. This study investigates microbial resistance within the lung microbiome using unsupervised machine learning approaches to uncover resistance patterns and potential clinical associations. it downloaded and selected lung microbiome data from HumanMetagenomeDB based on metadata characteristics such as relevant clinical information, patient demographics, environmental factors, and sample collection methods. The metadata was further complemented by details on antibiotic usage, disease status, and other relevant descriptions. The sequencing data underwent stringent quality control, followed by a functional profiling focus on identifying resistance genes through specialized databases like Antibiotic Resistance Database (CARD) which contains sequences of AMR gene sequence and resistance profiles. Subsequent analyses employed unsupervised machine learning techniques to unravel the structure and diversity of resistomes in the microbial community. Some of the methods employed were clustering methods such as K-Means and Hierarchical Clustering enabled the identification of sample groups based on their resistance gene profiles. The work was implemented in python, leveraging a range of libraries such as biopython for biological sequence manipulation, NumPy for numerical operations, Scikit-learn for machine learning, Matplotlib for data visualization and Pandas for data manipulation. The findings from this study provide insights into the distribution and dynamics of antimicrobial resistance within the lung microbiome. By leveraging unsupervised machine learning, we identified novel resistance patterns and potential drivers within the microbial community.

Keywords: antibiotic resistance, microbial community, unsupervised machine learning., sequences of AMR gene

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Authors: Emilio Galdeano-Gómez, Juan C. Pérez-Mesa, Laura Piedra-Muñoz, María C. García-Barranco, Jesús Hernández-Rubio

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The situation in which firms engage in simultaneous cooperation and competition with each other is a phenomenon known as co-opetition. This scenario has received increasing attention in business economics and management analyses. In the domain of supply chain networks and for small and medium-sized enterprises, SMEs, these strategies are of greater relevance given the complex environment of globalization and competition in open markets. These firms face greater challenges regarding technology and access to specific resources due to their limited capabilities and limited market presence. Consequently, alliances and collaborations with both buyers and suppliers prove to be key elements in overcoming these constraints. However, rivalry and competition are also regarded as major factors in successful internationalization processes, as they are drivers for firms to attain a greater degree of specialization and to improve efficiency, for example enabling them to allocate scarce resources optimally and providing incentives for innovation and entrepreneurship. The present work aims to contribute to the literature on SMEs’ internationalization strategies. The sample is constituted by a panel data of marketing firms from the Andalusian food sector and a multivariate regression analysis is developed, measuring variables of co-opetition and international activity. The hierarchical regression equations method has been followed, thus resulting in three estimated models: the first one excluding the variables indicative of channel type, while the latter two include the international retailer chain and wholesaler variable. The findings show that the combination of several factors leads to a complex scenario of inter-organizational relationships of cooperation and competition. In supply chain management analyses, these relationships tend to be classified as either buyer-supplier (vertical level) or supplier-supplier relationships (horizontal level). Several buyers and suppliers tend to participate in supply chain networks, and in which the form of governance (hierarchical and non-hierarchical) influences cooperation and competition strategies. For instance, due to their market power and/or their closeness to the end consumer, some buyers (e.g. large retailers in food markets) can exert an influence on the selection and interaction of several of their intermediate suppliers, thus endowing certain networks in the supply chain with greater stability. This hierarchical influence may in turn allow these suppliers to develop their capabilities (e.g. specialization) to a greater extent. On the other hand, for those suppliers that are outside these networks, this environment of hierarchy, characterized by a “hub firm” or “channel master”, may provide an incentive for developing their co-opetition relationships. These results prove that the analyzed firms have experienced considerable growth in sales to new foreign markets, mainly in Europe, dealing with large retail chains and wholesalers as main buyers. This supply industry is predominantly made up of numerous SMEs, which has implied a certain disadvantage when dealing with the buyers, as negotiations have traditionally been held on an individual basis and in the face of high competition among suppliers. Over recent years, however, cooperation among these marketing firms has become more common, for example regarding R&D, promotion, scheduling of production and sales.

Keywords: co-petition networks, international supply chain, maketing agrifood firms, SMEs strategies

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Authors: Luisa Barreira, Viana Castaneda, Maria J. Rodrigues, Florinda Gama, Tamara Santos, Marta Oliveira, Catarina Pereira, Maribela Pestana, Pedro Correia, Miguel Salazar, Carla Nunes, Luisa Custodio, Joao Varela

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In the last century, the world witnessed an exponential demographic increase that has put an enormous pressure on agriculture and food production. Associated also with climate changes, there has been a decrease in the amount of available freshwater and an increased salinization of soils which can affect the production of most food crops. Halophytes, however, are plants able to withstand high salinities while maintaining a good growth productivity. To cope with the excess salt, they produce secondary metabolites (e.g. vitamins and phenolic compounds) which, along with the natural presence of some minerals, makes them not only nutritionally rich but also functional foods. Some halophytes, as quinoa or salicornia, are already used in some countries, mostly as gourmet food. Hydroponic cultivation of halophytes using seawater or diluted seawater for watering can decrease the pressure on freshwater resources while producing a nutritional and functional food. The XtremeGourmet project funded by the EU aims to develop and optimize the production of different halophytes by hydroponics. One of the more specific objectives of this project is the study of halophytes’ productivity and chemical composition under different abiotic conditions, e.g. salt and nutrient concentration and light intensity. Three species of halophytes commonly occurring in saltmarshes of the South of Portugal (Inula chrithmoides, Salicornia ramosissima and Mesembryanthemum nodiflorum) were cultivated using hydroponics under different salinities, ranging from 5 to 45 dS/m. For each condition, several parameters were assessed namely: total and commercial productivity, electrical conductivity, total soluble solids, proximal composition, mineral profile, total phenolics, flavonoids and condensed tannins content and antioxidant activity. Results show that productivity was significantly reduced for all plants with increasing salinity up to salinity 29 dS/m and remained low onwards. Oppositely, the electrical conductivity and the total soluble solids content of the produced plants increased with salinity, reaching a plateau at 29 dS/m. It seems that plants reflect the salt concentration of the water up to some point, being able to regulate their salt content for higher salinities. The same tendency was observed for the ash content of these plants, which is related to the mineral uptake from the cultivating media and the plants’ capacity to both accumulate and regulate ions’ concentration in their tissues. Nonetheless, this comes with a metabolic cost which is observed by a decrease in productivity. The mineral profile of these plants shows high concentrations of sodium but also high amounts of potassium. In what concerns the microelements, these plants appear to be a good source of manganese and iron and the low amounts of toxic metals account for their safe consumption in moderate amounts. Concerning the phenolics composition, plants presented moderate concentrations of phenolics but high amounts of condensed tannins, particularly I. crithmoides which accounts for its characteristic sour and spicy taste. Contrary to some studies in which higher amounts of phenolics were found in plants cultivated under higher salinities, in this study, the highest amount of phenolic compounds were found in plants grown at the lowest or intermediate salinities. Nonetheless, there was a positive correlation between the concentration of these compounds and the antioxidant capacity of the plants’ extracts.

Keywords: functional properties, halophytes, hydroponics, nutritional composition, salinity effect

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Authors: Alberto Fina, Samuele Colonna, Maria del Mar Bernal, Orietta Monticelli, Mauro Tortello, Renato Gonnelli, Julio Gomez, Chiara Novara, Guido Saracco

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Thermally conductive polymer nanocomposites are of high interest for several applications including low-temperature heat recovery, heat exchangers in a corrosive environment and heat management in electronics and flexible electronics. In this paper, the preparation of thermally conductive nanocomposites exploiting graphene-related materials is addressed, along with their thermal characterization. In particular, correlations between 1- chemical and physical features of the nanoflakes and 2- processing conditions with the heat conduction properties of nanocomposites is studied. Polymers are heat insulators; therefore, the inclusion of conductive particles is the typical solution to obtain a sufficient thermal conductivity. In addition to traditional microparticles such as graphite and ceramics, several nanoparticles have been proposed, including carbon nanotubes and graphene, for the use in polymer nanocomposites. Indeed, thermal conductivities for both carbon nanotubes and graphenes were reported in the wide range of about 1500 to 6000 W/mK, despite such property may decrease dramatically as a function of the size, number of layers, the density of topological defects, re-hybridization defects as well as on the presence of impurities. Different synthetic techniques have been developed, including mechanical cleavage of graphite, epitaxial growth on SiC, chemical vapor deposition, and liquid phase exfoliation. However, the industrial scale-up of graphene, defined as an individual, single-atom-thick sheet of hexagonally arranged sp2-bonded carbons still remains very challenging. For large scale bulk applications in polymer nanocomposites, some graphene-related materials such as multilayer graphenes (MLG), reduced graphene oxide (rGO) or graphite nanoplatelets (GNP) are currently the most interesting graphene-based materials. In this paper, different types of graphene-related materials were characterized for their chemical/physical as well as for thermal properties of individual flakes. Two selected rGOs were annealed at 1700°C in vacuum for 1 h to reduce defectiveness of the carbon structure. Thermal conductivity increase of individual GNP with annealing was assessed via scanning thermal microscopy. Graphene nano papers were prepared from both conventional RGO and annealed RGO flakes. Characterization of the nanopapers evidenced a five-fold increase in the thermal diffusivity on the nano paper plane for annealed nanoflakes, compared to pristine ones, demonstrating the importance of structural defectiveness reduction to maximize the heat dissipation performance. Both pristine and annealed RGO were used to prepare polymer nanocomposites, by melt reactive extrusion. Thermal conductivity showed two- to three-fold increase in the thermal conductivity of the nanocomposite was observed for high temperature treated RGO compared to untreated RGO, evidencing the importance of using low defectivity nanoflakes. Furthermore, the study of different processing paremeters (time, temperature, shear rate) during the preparation of poly (butylene terephthalate) nanocomposites evidenced a clear correlation with the dispersion and fragmentation of the GNP nanoflakes; which in turn affected the thermal conductivity performance. Thermal conductivity of about 1.7 W/mK, i.e. one order of magnitude higher than for pristine polymer, was obtained with 10%wt of annealed GNPs, which is in line with state of the art nanocomposites prepared by more complex and less upscalable in situ polymerization processes.

Keywords: graphene, graphene-related materials, scanning thermal microscopy, thermally conductive polymer nanocomposites

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