71 research outputs found
MPath2PN - Translating Metabolic Pathways into Petri Nets
We propose MPath2PN, a tool which automatically translates metabolic pathways, as described in the major biological databases, into corresponding Petri net representations.
The aim is to allow for a systematic reuse, in the setting of metabolic pathways, of the variety of tools existing for Petri net analysis and simulation. The current prototype implementation of MPath2PN inputs the KEGG description of a metabolic pathway and produces two Petri nets, mainly differing for the treatment of ubiquitous substances. Such Petri nets are represented using PNML, a standard format for many Petri net tools. We are extending the tool by considering further formats for metabolic pathways in input and for Petri nets in output. MPath2PN is part of a more general project aimed at developing an integrated framework which should offer the possibility of automatically querying databases for metabolic pathways, producing corresponding Petri net models and performing analysis and simulation on them by means of various tools
Relación entre actividad física, gravedad clínica y perfil sociodemográfico en pacientes con Depresión Mayor
La actividad física está demostrando en los últimos años ser una buena estrategia antidepresiva complementaria para muchos pacientes. La asociación entre el grado de actividad física y las características clínicas y sociodemográficas en la Depresión aún no se ha estudiado suficientemente en muestras amplias y representativas de pacientes. Hacerlo es importante para obtener información que posibilite mejorar el diseño de programas destinados a promover la actividad física en estos pacientes. Se reclutaron 3374 pacientes con Depresión Mayor en tratamiento, que acudieron a consulta psiquiátrica por primera vez en Centros de Salud Mental distribuidos por toda España. Fueron clasificados en tres grupos de acuerdo con el nivel de actividad física semanal que declararon. En este estudio comparamos el grupo que comunicó mayor actividad física (n = 1033; 30.6%) con el que menos (n = 858; 25.4%). Los pacientes más activos tenían menor gravedad clínica de acuerdo con la puntuación en la escala Montgomery-Asberg Depression Rating Scale (MADRS). Además eran más jóvenes, con mejor nivel educativo y de empleo, menor aislamiento social y menor consumo de tabaco. Sin embargo, cuando todas estas variables fueron controladas, la diferencia en la puntuación en la MADRS seguía siendo estadísticamente significativa. De lo anterior deducimos que los pacientes depresivos con más edad o dificultades socioeconómicas tienden a hacer menos actividad física espontáneamente, por lo que probablemente necesiten un apoyo especial al recomendárselo.
Physical activity is showing in recent years to be a good antidepressant complementary strategy for many patients. The association between the degree of physical activity and clinical and sociodemographic characteristics in depression has still not been studied sufficiently in large and representative patient samples. Doing so is important to improve the design of programs that promote physical activity in depressive patients. 3374 patients with Major Depression who first came to psychiatric consultation in mental health centres in Spain were recruited. They were classified into three groups according to the level of weekly physical activity declared. In this study we compared the most physical activity declared group (n = 1033; 30.6%) with less physical activity declared group (n = 858; 25.4%). Most physically active patients had lower clinical depression severity according to the Montgomery-Asberg Depression Rating Scale (MADRS) scale. They were also younger, with higher education level and employment status; do not tend to live alone and less tobacco use. However, when all these variables were controlled, differences in MADRS Scores between groups remain statistically significant. Older and with socioeconomic difficulties depressive patients tend to do less physical activity, for this reason, it is probably that they need a particular support to recommend do exercise
Plant-derived bioactives and oxidative stress-related disorders: A key trend towards healthy aging and longevity promotion
Plants and their corresponding botanical preparations have been used for centuries due to their remarkable potential in both the treatment and prevention of oxidative stress-related disorders. Aging and aging-related diseases, like cardiovascular disease, cancer, diabetes, and neurodegenerative disorders, which have increased exponentially, are intrinsically related with redox imbalance and oxidative stress. Hundreds of biologically active constituents are present in each whole plant matrix, providing promissory bioactive effects for human beings. Indeed, the worldwide population has devoted increased attention and preference for the use of medicinal plants for healthy aging and longevity promotion. In fact, plant-derived bioactives present a broad spectrum of biological effects, and their antioxidant, anti-inflammatory, and, more recently, anti-aging effects, are considered to be a hot topic among the medical and scientific communities. Nonetheless, despite the numerous biological effects, it should not be forgotten that some bioactive molecules are prone to oxidation and can even exert pro-oxidant effects. In this sense, the objective of the present review is to provide a detailed overview of plant-derived bioactives in age-related disorders. Specifically, the role of phytochemicals as antioxidants and pro-oxidant agents is carefully addressed, as is their therapeutic relevance in longevity, aging-related disorders, and healthy-aging promotion. Finally, an eye-opening look into the overall evidence of plant compounds related to longevity is present
Tuneable nature of metal organic frameworks as heterogeneous solid catalysts for alcohol oxidation
[EN] Selective benzyl alcohol oxidation (BA) to benzaldehyde has been frequently used as a benchmark reaction to evaluate the catalytic activity of metal organic frameworks (MOFs) as oxidation catalysts. Substituted BAs, and aliphatic and allylic alcohols have also been often used as substrates in these studies. In the present review, the current state of the art of MOFs as heterogeneous catalysts for the oxidation of BA and other alcohols is described, grouping the reports according to the nature of the active sites present on the MOFs. Thus, MOFs in which the catalytic centres are located at the ligands, at metallic nodes, or at metal nanoparticles (MNPs) incorporated within the MOF pores and photoassisted oxidations have been commented on. The aim of this review is to stress the current limitations encountered in the use of MOFs, particularly with respect to MOF stability and activity and propose new targets in the area.AD thanks the University Grants Commission (UGC), New Delhi, for the award of an Assistant Professorship under its Faculty Recharge Programme. AD also thanks the Department of Science and Technology, India, for the financial support through Extra Mural Research Funding (EMR/2016/006500). Financial support from the Spanish Ministry of Economy and Competitiveness (Severo Ochoa and CTQ2015-69153-CO2-1) is gratefully acknowledged.Dhakshinamoorthy, A.; Asiri, AM.; García Gómez, H. (2017). Tuneable nature of metal organic frameworks as heterogeneous solid catalysts for alcohol oxidation. Chemical Communications. 53(79):10851-10869. https://doi.org/10.1039/c7cc05927bS1085110869537
Diel in situ picophytoplankton cell death cycles coupled with cell division
The diel variability in picophytoplankton cell death was analyzed by quantifying the proportion of dead cyanobacteria Prochlorococcus and Synechococcus cells along several in situ diel cycles in the open Mediterranean Sea. During the diel cycle, total cell abundance varied on average 2.8 +/- 0.6 and 2.6 +/- 0.4 times for Synechococcus and Prochlorococcus populations, respectively. Increasing percentages of dead cells of Prochlorococcus and Synechococcus were observed during the course of the day reaching the highest values around dusk and decreasing as the night progressed, indicating a clear pattern of diel variation in the cell mortality of both cyanobacteria. Diel cycles of cell division were also monitored. The maximum percentage of dead cells (Max % DC) and the G2 + M phase of the cell division occurred within a period of 2 h for Synechoccoccus and 4.5 h for Prochlorococcus, and the lowest fraction of dead cells occurred at early morning, when the maximum number of cells in G1 phase were also observed. The G1 maximum corresponded with the maximal increase in newly divided cells (minimum % dead cells), and the subsequent exposure of healthy daughter cells to environmental stresses during the day resulted in the progressive increase in dying cells, with the loss of these cells from the population when cell division takes place. The discovery of diel patterns in cell death observed revealed the intense dynamics of picocyanobacterial populations in nature
Exploring the expressiveness of abstract metabolic networks
Metabolism is characterised by chemical reactions linked to each other, creating a complex network structure. The whole metabolic network is divided into pathways of chemical reactions, such that every pathway is a metabolic function. A simplified representation of metabolism, which we call an abstract metabolic network, is a graph in which metabolic pathways are nodes and there is an edge between two nodes if their corresponding pathways share one or more compounds. The abstract metabolic network of a given organism results in a small network that requires low computational power to be analysed and makes it a suitable model to perform a large-scale comparison of organisms’ metabolism. To explore the potentials and limits of such a basic representation, we considered a comprehensive set of KEGG organisms, represented through their abstract metabolic network. We performed pairwise comparisons using graph kernel methods and analyse the results through exploratory data analysis and machine learning techniques. The results show that abstract metabolic networks discriminate macro evolutionary events, indicating that they are expressive enough to capture key steps in metabolism evolution
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