Fitorremediación asistida a través de bacterias, para suelos contaminados con metales pesados y plaguicidas

TANIA GÓMEZ MORALES (2023, [Otro, Trabajo terminal, especialidad])

El suelo es un recurso no renovable que nos proporciona diferentes beneficios, incluidos los servicios ecosistémicos. Sin embargo, actividades antropogénicas como la minería y la agricultura lo han contaminado. Las prácticas mineras y agrícolas liberan contaminantes como plaguicidas y metales pesados al suelo como contaminantes individuales o mezclas, generando importantes efectos adversos para el ambiente y la salud humana. Debido a esta problemática, se han desarrollado diferentes estrategias de remediación para sitios con presencia de estos co-contaminantes. Una de ellas es la fitorremediación asistida por bacterias, una técnica basada en la asociación de plantas y bacterias, donde ambos organismos se benefician y mejoran la eficiencia de la remediación.

Soil is a non-renewable resource that provides us with different benefits, including ecosystem services. However, anthropogenic activities such as mining and agriculture have contaminated it. Minery and agriculture practices release contaminants such as pesticides and heavy metals into the soil as individual pollutants or mixtures, generating important adverse environmental and human health effects. Due to this problem, different remediation strategies have been developed for sites with the presence of these co-contaminants; one of them is bacterial-assisted phytoremediation, a technique based on the association of plants and bacteria, where both organisms benefit and improve remediation efficiency.

BIOLOGÍA Y QUÍMICA CIENCIAS DE LA VIDA suelo, fitorremediación, bacterias, plaguicidas, metales pesados, co-contaminados. soil, phytoremediation, bacteria, pesticides, heavy metals, co-contaminated

Contratos inteligentes para la gestión de datos de sensado móvil y vestible para aplicaciones en salud

Smart contracts for mobile and wearable sensing data management for health applications

José Ricardo Cedeño García (2023, [Tesis de maestría])

El aumento en la producción de datos derivado de la adopción de tecnologías móviles y de IoT está revolucionando la salud, pero también plantea importantes retos éticos y de privacidad. Los recientes avances en el aprendizaje automático han resaltado la importancia de recopilar y etiquetar datos correctamente, en especial para fines críticos, como el desarrollo de aplicaciones para cuidados médicos. La recopilación de datos médicos para tareas de aprendizaje automático presenta limitaciones en cuanto a la cantidad, variedad y calidad de las fuentes disponibles. Una forma de abordar este dilema es el uso de Blockchain para la recopilación y el uso de datos de pacientes. El anonimato de una red centralizada permite proteger la identidad del paciente. La estructura formada por nodos permite que la información esté siempre disponible y no dependa de un servidor principal. La inmutabilidad de los registros en la cadena garantiza la trazabilidad inequívoca del flujo de los datos del paciente. Por último, los mecanismos de consenso y recompensa de la red podrían motivar a nuevos usuarios a participar del sensado activo. Presentamos TRHEAD, una arquitectura de referencia basada en la Blockchain para recopilar datos sanitarios, firmar consentimientos, anotar datos y obtener crédito por los mismos, permitiendo a los usuarios rastrear el uso de sus datos, a los científicos rastrear su procedencia y proteger al mismo tiempo la privacidad de los pacientes. Exponemos dos implementaciones de nuestra arquitectura aplicadas a distintas campañas de sensado para comprobar su viabilidad, así como los resultados de su aplicación en estos escenarios y las conclusiones que desprendieron de su análisis. Dado que uno de los objetivos principales de TRHEAD es la recopilación de datos mediante sensado activo para el entrenamiento legal/consciente de modelos de aprendizaje automático, se realizó el entrenamiento de un modelo con los datos obtenidos de la campaña de sensado correspondiente a imágenes de rostros humanos, con el fin de detectar estados de ánimo. Finalmente se discute el papel de TRHEAD en el aseguramiento del trato justo y consciente de la información de los pacientes y el camino por recorrer en el perfeccionamiento de la arquitectura.

The increase in data production resulting from the adoption of mobile and IoT technologies is revolutionizing healthcare, but it also poses significant ethical and privacy challenges. Recent advances in machine learning have highlighted the importance of collecting and labeling data correctly, especially for critical purposes such as deploying healthcare software. Collecting medical data for machine learning tasks presents limitations in terms of the quantity, variety, and quality of available sources. One way to address this dilemma is the use of Blockchain for the collection and use of patient data. The anonymity of a centralized network allows the patient’s identity to be protected. The structure formed by nodes allows information to be always available and not dependent on a main server. The immutability of the records in the chain guarantees the unequivocal traceability of the flow of patient data. Finally, the network’s consensus and reward mechanisms could motivate new users to participate in active sensing. We present TRHEAD, a Blockchain-based reference architecture for collecting healthcare data, signing consents, annotating data and getting credit for it, allowing users to track the use of their data, scientists to track its provenance while protecting patients privacy. We present two implementations of our architecture applied to different sensing campaigns to test their feasibility, as well as the results of their application in these scenarios and the conclusions drawn from those results. Since one of the main objectives of TRHEAD is the collection of data through active sensing for the legal/conscious training of machine learning models, a model was trained with the data obtained from the sensing campaign corresponding to images of human faces, in order to detect moods. Finally, the role of TRHEAD in ensuring the fair and conscientious treatment of patient information and the road ahead in refining the architecture is discussed.

Contratos Inteligentes, Blockchain, Privacidad, Aprendizaje de Máquina Etico, Recopilación Consciente de Datos, Consentimiento, Arquitectura de Referencia Smart Contracts, Blockchain, Privacy, Ethical Machine Learning, Conscious Data Collection, Consent, Reference Architecture INGENIERÍA Y TECNOLOGÍA CIENCIAS TECNOLÓGICAS TECNOLOGÍA DE LOS ORDENADORES INTELIGENCIA ARTIFICIAL INTELIGENCIA ARTIFICIAL

Competencia socioemocional y toma de decisiones en el rendimiento académico de estudiantes universitarios

MAYRA DELGADO VILLALOBOS (2023, [Tesis de doctorado])

Las emociones sociales forman parte de la complejidad interna de una sociedad donde

confluyen niveles de estructura social: las interacciones entre sus individuos, los patrones

de relación entre ellos y sus principios de organización. Las emociones sociales subyacen

a esta complejidad e incluyen mecanismos de autorregulación que permiten a los

individuos desarrollar habilidades socioemocionales para evaluar cuándo y con quién

cooperar o competir, regular las respuestas emocionales y el comportamiento en

situaciones sociales, mantener relaciones de largo plazo, favorecer la prosocialidad y la

cohesión grupal. Estas habilidades son fundamentales en nuestros entornos culturales

dinámicos. Por ello, la OECD las considera habilidades del siglo XXI.

Desde una perspectiva interdisciplinar con énfasis en la cognición social, en la

presente investigación se revisó la importancia y la función de las emociones sociales, y

con base en los diferentes niveles de complejidad social se propone una distinción entre

habilidades y competencias socioemocionales. También se revisaron diversos enfoques

teóricos sobre estas competencias, así como la metodología para su evaluación en la

educación universitaria. Asimismo, se realizó un estudio exploratorio con un diseño

transversal y la muestra se conformó por 104 estudiantes universitarios. El modelo teórico

propuesto se probó mediante ecuaciones estructurales, encontrándose diferencias

significativas entre el compromiso académico y el rendimiento académico, la resiliencia

y el razonamiento.

Social emotions are part of the internal complexity of a society where levels of social

structure converge: the interactions between its individuals, the relationships patterns

between them and their organizational principles. Social emotions underlie this

complexity and include self-regulation mechanisms that allow individuals to develop

socioemotional skills to assess when and with whom to cooperate or compete, regulate

emotional responses and behavior in social situations, maintain long-term relationships,

promote prosociality and group cohesion. These skills are essential in our dynamic

cultural environments. For this reason, the OECD considers them 21st century skills.

From an interdisciplinary perspective with an emphasis on social cognition, this

research reviewed the importance and function of social emotions, and based on the

different levels of social complexity, a distinction between socio-emotional skills and

competencies is proposed. Various theoretical approaches to these competencies were

also reviewed, as well as the methodology for their evaluation in university education.

Likewise, an exploratory study was carried out with a cross-sectional design and the

sample consisted of 104 university students. The proposed theoretical model was tested

using structural equations, finding significant differences between academic commitment

and academic performance, resilience and reasoning.

HUMANIDADES Y CIENCIAS DE LA CONDUCTA PEDAGOGÍA cognición social, desarrollo socioemocional, competencias socioemocionales, evaluación socioemocional y aprendizaje socioemocional. social cognition, social-emotional development, social-emotional competencies, social-emotional assessment and social-emotional learning

Control de sistemas usando aprendizaje de máquina

Systems control using machine learning

Jesús Martín Miguel Martínez (2023, [Tesis de maestría])

El aprendizaje por refuerzo es un paradigma del aprendizaje de máquina con un amplio desarrollo y una creciente demanda en aplicaciones que involucran toma de decisiones y control. Es un paradigma que permite el diseño de controladores que no dependen directamente del modelo que describe la dinámica del sistema. Esto es importante ya que en aplicaciones reales es frecuente que no se disponga de dichos modelos de manera precisa. Esta tesis tiene como objetivo implementar un controlador óptimo en tiempo discreto libre de modelo. La metodología elegida se basa en algoritmos de aprendizaje por refuerzo, enfocados en sistemas con espacios de estado y acción continuos a través de modelos discretos. Se utiliza el concepto de función de valor (Q-función y función V ) y la ecuación de Bellman para resolver el problema del regulador cuadrático lineal para un sistema mecánico masa-resorte-amortiguador, en casos donde se tiene conocimiento parcial y desconocimiento total del modelo. Para ambos casos las funciones de valor son definidas explícitamente por la estructura de un aproximador paramétrico, donde el vector de pesos del aproximador es sintonizado a través de un proceso iterativo de estimación de parámetros. Cuando se tiene conocimiento parcial de la dinámica se usa el método de aprendizaje por diferencias temporales en un entrenamiento episódico, que utiliza el esquema de mínimos cuadrados con mínimos cuadrados recursivos en la sintonización del crítico y descenso del gradiente en la sintonización del actor, el mejor resultado para este esquema es usando el algoritmo de iteración de valor para la solución de la ecuación de Bellman, con un resultado significativo en términos de precisión en comparación a los valores óptimos (función DLQR). Cuando se tiene desconocimiento de la dinámica se usa el algoritmo Q-learning en entrenamiento continuo, con el esquema de mínimos cuadrados con mínimos cuadrados recursivos y el esquema de mínimos cuadrados con descenso del gradiente. Ambos esquemas usan el algoritmo de iteración de política para la solución de la ecuación de Bellman, y se obtienen resultados de aproximadamente 0.001 en la medición del error cuadrático medio. Se realiza una prueba de adaptabilidad considerando variaciones que puedan suceder en los parámetros de la planta, siendo el esquema de mínimos cuadrados con mínimos cuadrados recursivos el que tiene los mejores resultados, reduciendo significativamente ...

Reinforcement learning is a machine learning paradigm with extensive development and growing demand in decision-making and control applications. This technique allows the design of controllers that do not directly depend on the model describing the system dynamics. It is useful in real-world applications, where accurate models are often unavailable. The objective of this work is to implement a modelfree discrete-time optimal controller. Through discrete models, we implemented reinforcement learning algorithms focused on systems with continuous state and action spaces. The concepts of value-function, Q-function, V -function, and the Bellman equation are employed to solve the linear quadratic regulator problem for a mass-spring-damper system in a partially known and utterly unknown model. For both cases, the value functions are explicitly defined by a parametric approximator’s structure, where the weight vector is tuned through an iterative parameter estimation process. When partial knowledge of the dynamics is available, the temporal difference learning method is used under episodic training, utilizing the least squares with a recursive least squares scheme for tuning the critic and gradient descent for the actor´s tuning. The best result for this scheme is achieved using the value iteration algorithm for solving the Bellman equation, yielding significant improvements in approximating the optimal values (DLQR function). When the dynamics are entirely unknown, the Q-learning algorithm is employed in continuous training, employing the least squares with recursive least squares and the gradient descent schemes. Both schemes use the policy iteration algorithm to solve the Bellman equation, and the system’s response using the obtained values was compared to the one using the theoretical optimal values, yielding approximately zero mean squared error between them. An adaptability test is conducted considering variations that may occur in plant parameters, with the least squares with recursive least squares scheme yielding the best results, significantly reducing the number of iterations required for convergence to optimal values.

aprendizaje por refuerzo, control óptimo, control adaptativo, sistemas mecánicos, libre de modelo, dinámica totalmente desconocida, aproximación paramétrica, Q-learning, iteración de política reinforcement learning, optimal control, adaptive control, mechanical systems, modelfree, utterly unknown dynamics, parametric approximation, Q-learning, policy iteration INGENIERÍA Y TECNOLOGÍA CIENCIAS TECNOLÓGICAS TECNOLOGÍA DE LOS ORDENADORES INTELIGENCIA ARTIFICIAL INTELIGENCIA ARTIFICIAL

The Pacific harbor seal gut microbiota in Mexico: Its relationship with diet and functional inferences

ARLETTE MARIMAR PACHECO SANDOVAL (2019, [Artículo])

Diet is a primary driver of the composition of gut microbiota and is considered one of the main routes of microbial colonization. Prey identification is fundamental for correlating the diet with the presence of particular microbial groups. The present study examined how diet influenced the composition and function of the gut microbiota of the Pacific harbor seal (Phoca vitulina richardii) in order to better understand the role of prey consumption in shaping its microbiota. This species is a good indicator of the quality of the local environment due to both its foraging and haul-out site fidelity. DNA was extracted from 20 fecal samples collected from five harbor seal colonies located in Baja California, Mexico. The V4 region of 16S rRNA gene was amplified and sequenced using the Illumina technology. Results showed that the gut microbiota of the harbor seals was dominated by the phyla Firmicutes (37%), Bacteroidetes (26%) and Fusobacteria (26%) and revealed significant differences in its composition among the colonies. Funtional analysis using the PICRUSt software suggests a high number of pathways involved in the basal metabolism, such as those for carbohydrates (22%) and amino acids (20%), and those related to the degradation of persistent environmental pollutants. In addition, a DNA metabarcoding analysis of the same samples, via the amplification and sequencing of the mtRNA 16S and rRNA 18S genes, was used to identify the prey consumed by harbor seals revealing the consumption of prey with mainly demersal habits. Functional redundancy in the seal gut microbiota was observed, irrespective of diet or location. Our results indicate that the frequency of occurrence of specific prey in the harbor seal diet plays an important role in shaping the composition of the gut microbiota of harbor seals by influencing the relative abundance of specific groups of gut microorganisms. A significant relationship was found among diet, gut microbiota composition and OTUs assigned to a particular metabolic pathway. © 2019 Pacheco-Sandoval et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

RNA 16S, RNA 18S, amino acid analysis, animal food, Article, bacterium colony, Bacteroidetes, basal metabolic rate, biodegradation, controlled study, DNA barcoding, feces analysis, Firmicutes, Fusobacteria, intestine flora, metabolism, Mexico, microb BIOLOGÍA Y QUÍMICA CIENCIAS DE LA VIDA BIOLOGÍA ANIMAL (ZOOLOGÍA) BIOLOGÍA ANIMAL (ZOOLOGÍA)

Dual function of EDTA with silver nanoparticles for root canal treatment–A novel modification

JUAN MANUEL MARTINEZ ANDRADE (2018, [Artículo])

The chelating and antimicrobial capacity of a novel modification of 17% EDTA with silver nanoparticles (AgNPs) (EDTA-AgNPs) was evaluated in-vitro for root canal treatment (RCT). The EDTA-AgNPs solution was characterized by UV-Vis spectroscopy, ?-potential and high-resolution transmission electron microscopy (HRTEM). Antimicrobial capacity was evaluated against Candida albicans and Staphylococcus aureus in planktonic and biofilm cells by broth macrodilution (24 h) and XTT assays, (1, 10 and 30 min) respectively. The chelating capacity of EDTA-AgNPs was assessed indirectly (smear layer removal) and directly (demineralizing effect) in bovine dentin at two silver concentrations, 16 and 512 ?g/ ml at 1 and 10 minutes of exposure time. Smear layer removal was evaluated by atomic force microscopy (AFM) and scanning electron microscopy (SEM). The demineralizing effect was determined by atomic absorption spectroscopy (AAS), microhardness test (MH) and X-ray diffractometer (XRD). Synthesized AgNPs were quasi-spherical in shape with an average size of 13.09 ± 8.05 nm. 17% EDTA-AgNPs was effective to inhibit C. albicans and S. aureus in planktonic and biofilm cultures. The smear layer removal and demineralizing effect were similar between 17% EDTA-AgNPs and 17% EDTA treatments. The 17% EDTA-AgNPs solution proved to be an effective antimicrobial agent, and has a similar chelating capacity to 17% EDTA alone. These in-vitro studies strongly suggest that EDTA-AgNPs could be used for effective smear layer removal, having an antimicrobial effect at the same time during RCT. © 2018 Martinez-Andrade et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

edetic acid, silver nanoparticle, edetic acid, metal nanoparticle, silver, antibacterial activity, antibiotic sensitivity, antifungal activity, antimicrobial activity, Article, atomic absorption spectrometry, atomic force microscopy, biofilm, bovine, BIOLOGÍA Y QUÍMICA CIENCIAS DE LA VIDA MICROBIOLOGÍA MICROBIOLOGÍA

Reconocimiento continuo de la Lengua de Señas Mexicana

Continuous recognition of Mexican Sign Language

Ricardo Fernando Morfín Chávez (2023, [Tesis de maestría])

La Lengua de Señas Mexicana (LSM) es la lengua utilizada por la comunidad Sorda en México, y, a menudo, subestimada y pasada por alto por la comunidad oyente, lo que resulta en la exclusión sistemática de las personas Sordas en diversos aspectos de la vida. Sin embargo, la tecnología puede desempeñar un papel fundamental en acercar a la comunidad Sorda con la comunidad oyente, promoviendo una mayor inclusión y comprensión entre ambas. El objetivo principal de este trabajo es diseñar, implementar y evaluar un sistema de reconocimiento continuo de señas estáticas en LSM mediante, visión por computadora y técnicas de aprendizaje máquina. Se establecieron objetivos específicos, que incluyen la generación de un conjunto de datos de señas estáticas, pertenecientes al alfabeto manual de la LSM, el diseño de un modelo de reconocimiento, y la evaluación del sistema, tanto en la modalidad aislada como en la continua. La metodología involucra dos evaluaciones distintas. La primera se enfoca en el reconocimiento de señas estáticas en el dominio aislado, para ello se capturaron datos de 20 participantes realizando movimientos de la mano en múltiples ángulos. Se evaluaron diversas técnicas de aprendizaje automático, destacando que el enfoque basado en Máquinas de Soporte Vectorial (SVM) obtuvo los mejores resultados (F1-Score promedio del 0.91). La segunda evaluación se concentra en el reconocimiento continuo de señas estáticas, con datos recopilados de seis participantes con diferentes niveles de competencia en LSM, logrando un rendimiento sólido con errores cercanos al 7 %. Además, se evaluó la viabilidad del sistema en aplicaciones de tiempo real, demostrando un excelente desempeño (velocidad promedio de procesamiento de 45 cuadros por segundo). A pesar de los logros alcanzados, es importante reconocer que este proyecto se centró en el reconocimiento continuo de señas estáticas en LSM. Queda pendiente, como un desafío interesante, la exploración del reconocimiento continuo de señas dinámicas en LSM para futuras investigaciones. Se considera esencial explorar enfoques orientados a la escalabilidad y aplicaciones en tiempo real en investigaciones posteriores.

This study focuses on the continuous recognition of static signs in Mexican Sign Language (Lengua de Señas Mexicana (LSM)), the language used by the Deaf community in Mexico. Despite its significance, LSM is often underestimated and overlooked, leading to the systematic exclusion of Deaf individuals in various aspects of life. The primary objective of this work is to design, implement, and evaluate a continuous static sign recognition system in LSM using computer vision and machine learning techniques. Specific goals were established, including the creation of a dataset of static signs belonging to the manual alphabet of LSM, the design of a recognition model, and the evaluation of the system in both isolated and continuous modes. The methodology involves two distinct evaluations. The first one focuses on the recognition of static signs in the isolated domain, for which data from 20 participants performing hand movements at various angles were collected. Various machine learning techniques were evaluated, with the Máquinas de Soporte Vectorial (SVM)-based approach achieving the best results (average F1-Score of 0.91). The second evaluation centers on the continuous recognition of static signs, using data collected from six participants with varying levels of competence in LSM, achieving robust performance with errors close to 7 %. Furthermore, the feasibility of the system in real-time applications was assessed, demonstrating excellent performance (average processing speed of 45 frames per second). Despite the achievements, it is important to recognize that this project focused on continuous recognition of static signs in LSM. It remains an interesting challenge to explore the continuous recognition of dynamic signs in LSM for future research. It is considered essential to explore scalability-oriented approaches and real-time applications in subsequent investigations.

Lengua de Señas Mexicana (LSM), visión por computadora, aprendizaje automático, alfabeto manual de la LSM, reconocimiento automático de señas estáticas, reconocimiento aislado de señas, reconocimiento continuo de señas, aplicacion Mexican Sign Language (LSM), computer vision, machine learning, LSM manual alpahbet, automatic recognition of static signs, isolated sign recognition, continuous sign recognition, real-time aplications INGENIERÍA Y TECNOLOGÍA CIENCIAS TECNOLÓGICAS TECNOLOGÍA DE LOS ORDENADORES ENSEÑANZA CON AYUDA DE ORDENADOR ENSEÑANZA CON AYUDA DE ORDENADOR

Effect of antimicrobial nanocomposites on Vibrio cholerae lifestyles: Pellicle biofilm, planktonic and surface-attached biofilm

ANAID MEZA VILLEZCAS (2019, [Artículo])

Vibrio cholerae is an important human pathogen causing intestinal disease with a high incidence in developing countries. V. cholerae can switch between planktonic and biofilm lifestyles. Biofilm formation is determinant for transmission, virulence and antibiotic resistance. Due to the enhanced antibiotic resistance observed by bacterial pathogens, antimicrobial nanomaterials have been used to combat infections by stopping bacterial growth and preventing biofilm formation. In this study, the effect of the nanocomposites zeolite-embedded silver (Ag), copper (Cu), or zinc (Zn) nanoparticles (NPs) was evaluated in V. cholerae planktonic cells, and in two biofilm states: pellicle biofilm (PB), formed between air-liquid interphase, and surface-attached biofilm (SB), formed at solid-liquid interfaces. Each nanocomposite type had a distinctive antimicrobial effect altering each V. cholerae lifestyles differently. The ZEO-AgNPs nanocomposite inhibited PB formation at 4 μg/ml, and prevented SB formation and eliminated planktonic cells at 8 μg/ml. In contrast, the nanocomposites ZEO-CuNPs and ZEO-ZnNPs affect V. cholerae viability but did not completely avoid bacterial growth. At transcriptional level, depending on the nanoparticles and biofilm type, nanocomposites modified the relative expression of the vpsL, rbmA and bap1, genes involved in biofilm formation. Furthermore, the relative abundance of the outer membrane proteins OmpT, OmpU, OmpA and OmpW also differs among treatments in PB and SB. This work provides a basis for further study of the nanomaterials effect at structural, genetic and proteomic levels to understand the response mechanisms of V. cholerae against metallic nanoparticles. © 2019 Meza-Villezcas et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

bacterial protein, copper nanoparticle, nanocomposite, OmpT protein, OmpU protein, OmpW protein, outer membrane protein A, silver nanoparticle, unclassified drug, zeolite, zinc nanoparticle, antiinfective agent, copper, metal nanoparticle, nanocompos BIOLOGÍA Y QUÍMICA CIENCIAS DE LA VIDA MICROBIOLOGÍA MICROBIOLOGÍA

Enhancement of antibiotics antimicrobial activity due to the silver nanoparticles impact on the cell membrane

Roberto Vazquez-Munoz (2019, [Artículo])

The ability of microorganisms to generate resistance outcompetes with the generation of new and efficient antibiotics; therefore, it is critical to develop novel antibiotic agents and treatments to control bacterial infections. An alternative to this worldwide problem is the use of nanomaterials with antimicrobial properties. Silver nanoparticles (AgNPs) have been extensively studied due to their antimicrobial effect in different organisms. In this work, the synergistic antimicrobial effect of AgNPs and conventional antibiotics was assessed in Gram-positive and Gram-negative bacteria. AgNPs minimal inhibitory concentration was 10–12 μg mL-1 in all bacterial strains tested, regardless of their different susceptibility against antibiotics. Interestingly, a synergistic antimicrobial effect was observed when combining AgNPs and kanamycin according to the fractional inhibitory concentration index, FICI: <0.5), an additive effect by combining AgNPs and chloramphenicol (FICI: 0.5 to 1), whereas no effect was found with AgNPs and β-lactam antibiotics combinations. Flow cytometry and TEM analysis showed that sublethal concentrations of AgNPs (6–7 μg mL-1) altered the bacterial membrane potential and caused ultrastructural damage, increasing the cell membrane permeability. No chemical interactions between AgNPs and antibiotics were detected. We propose an experimental supported mechanism of action by which combinatorial effect of antimicrobials drives synergy depending on their specific target, facilitated by membrane alterations generated by AgNPs. Our results provide a deeper understanding about the synergistic mechanism of AgNPs and antibiotics, aiming to combat antimicrobial infections efficiently, especially those by multi-drug resistant microorganisms, in order to mitigate the current crisis due to antibiotic resistance. © 2019 Vazquez-Muñoz et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

ampicillin, antibiotic agent, aztreonam, beta lactam antibiotic, biapenem, chloramphenicol, kanamycin, silver nanoparticle, silver nitrate, antiinfective agent, metal nanoparticle, silver, antibiotic sensitivity, antimicrobial activity, Article, bact BIOLOGÍA Y QUÍMICA CIENCIAS DE LA VIDA BIOFÍSICA BIOFÍSICA

High quality diet improves lipid metabolic profile and breeding performance in the blue-footed booby, a long-lived seabird

ERICK GONZALEZ MEDINA (2018, [Artículo])

Understanding the role of diet in the physiological condition of adults during reproduction and hence its effect on reproductive performance is fundamental to understand reproductive strategies in long-lived animals. In birds, little is known about the influence of the quality of food consumed at the beginning of the reproductive period and its short-term effects on reproductive performance. To assess the role of diet in the physiological condition of female blue-footed booby, Sula nebouxii (BFBO), during reproduction we evaluated whether individual differences in diet (assessed by using δ13C and δ15N values of whole blood from female birds and muscle tissue of the principal prey species) prior to egg laying and during incubation influenced their lipid metabolic profile (measured as triglyceride levels and C:N ratio) and their reproductive performance (defined by laying date, clutch size and hatching success). Females with higher δ15N values in their blood during the courtship and incubation periods had a higher lipid metabolic profile, earlier laying date, greater clutch size (2–3 eggs) and higher hatching success. Females that laid earlier and more eggs (2–3 eggs) consumed more Pacific anchoveta (Cetengraulis mysticetus) and Pacific thread herring (Opisthonema libertate) than did other females. These two prey species also had high amounts of lipids (C:N ratio) and caloric content (Kcal/g fresh weight). The quality of food consumed by females at the beginning of reproduction affected their physiological condition, as well as their short-term reproductive performance. Our work emphasizes the importance of determining the influence of food quality during reproduction to understand the reproductive decisions and consequences in long-lived animals. © 2018 González-Medina et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

nitrogen 15, triacylglycerol, lipid, animal experiment, Article, breeding, carbon nitrogen ratio, clutch size, controlled study, courtship, diet, egg laying, female, food intake, hatching, lipid metabolism, muscle tissue, nonhuman, prey, reproduction CIENCIAS FÍSICO MATEMÁTICAS Y CIENCIAS DE LA TIERRA CIENCIAS DE LA TIERRA Y DEL ESPACIO OCEANOGRAFÍA OCEANOGRAFÍA