Quantitative image analysis of polyhydroxyalkanoates inclusions from microbial mixed cultures under different SBR operation strategies

Polyhydroxyalkanoates (PHAs) produced from mixed microbial cultures (MMC), regarded as potential substitutes of petrochemical plastics, can be found as intracellular granules in various microorganisms under limited nutrient conditions and excess of carbon source. PHA is traditionally quantified by laborious and time-consuming chromatography analysis, and a simpler and faster method to assess PHA contents from MMC, such as quantitative image analysis (QIA), is of great interest. The main purpose of the present work was to upgrade a previously developed QIA methodology (Mesquita et al., 2013a, 2015) for MMC intracellular PHA contents quantification, increase the studied intracellular PHA concentration range and extend to different sequencing batch reactor (SBR) operation strategies. Therefore, the operation of a new aerobic dynamic feeding (ADF) SBR allowed further extending the studied operating conditions, dataset, and range of the MMC intracellular PHA contents from the previously reported anaerobic/aerobic cycle SBR. Nile Blue A (NBA) staining was employed for epifluorescence microscope visualization and image acquisition, further fed to a custom developed QIA. Data from each of the feast and famine cycles of both SBR were individually processed using chemometrics analysis, obtaining the correspondent partial least squares (PLS) models. The PHA concentrations determined from PLS models were further plotted against the results obtained in the standard chromatographic method. For both SBR the predicted ability was higher at the end of the feast stage than for the famine stage. Indeed, an independent feast and famine QIA data treatment was found to be fundamental to obtain the best prediction abilities. Furthermore, a promising overall correlation (R2 of 0.83) could be found combining the overall QIA data regarding the PHA prediction up to a concentration of 1785.1 mgL-1 (37.3 wt%). Thus, the results confirm that the presented QIA methodology can be seen as promising for estimating higher intracellular PHA concentrations for a larger reactors operation systems and further extending the prediction range of previous studies.This study was supported by the Portuguese Foundation for Science and Technology (FCT) under the scope of the strategic funding of UID/BIO/04469/2013 unit and COMPETE 2020 (POCI-01-0145-FEDER-006684) and BioTecNorte operation (NORTE01-0145-FEDER-000004) funded by European Regional Development Fundunder the scope ofNorte2020 - ProgramaOperacional Regional do Norte.The authors also acknowledge the financial support to Cristiano S. Leal (PTDC/EBB-EBI/103147/2008, FCOMP-01-0124-FEDER009704) and Daniela P. Mesquita through the FCT postdoctoral grant (SFRH/BPD/82558/2011).info:eu-repo/semantics/publishedVersio

Kerteszia subgenus of Anopheles associated with the Brazilian Atlantic rainforest:current knowledge and future challenges

Background: The Atlantic rainforest ecosystem, where bromeliads are abundant, provides an excellent environment for Kerteszia species, because these anophelines use the axils of those plants as larval habitat. Anopheles (K.) cruzii and Anopheles (K.) bellator are considered the primary vectors of malaria in the Atlantic forest. Although the incidence of malaria has declined in some areas of the Atlantic forest, autochthonous cases are still registered every year, with Anopheles cruzii being considered to be a primary vector of both human and simian Plasmodium. Methods: Recent publications that addressed ecological aspects that are important for understanding the involvement of Kerteszia species in the epidemiology of malaria in the Atlantic rainforest in the Neotropical Region were analysed. Conclusion: The current state of knowledge about Kerteszia species in relation to the Atlantic rainforest ecosystem was discussed. Emphasis was placed on ecological characteristics related to epidemiological aspects of this group of mosquitoes. The main objective was to investigate biological aspects of the species that should be given priority in future studie

Chaos and pattern formation in a spatial tritrophic food chain

The model of Hastings and Powell describes a tritrophic food chain that exhibits chaotic dynamics. The model assumes that the populations are homogeneously mixed, so that the probability that any two individuals interact is uniform and space can be ignored. In this paper we propose a spatial version of the Hastings and Powell model in which predators seek their preys only in a finite neighborhood of their home location, breaking the mixing hypothesis. Treating both space and time as discrete variables we derive a set of coupled equations that describe the evolution of the populations at each site of the spatial domain. We show that the introduction of local predator-prey interactions result in qualitatively distinct dynamics of predator and prey populations. The evolution equations for the predators involve averages over the local density of preys, whereas the equations for the preys involve double averages, where the local density of both preys and predators appear. Our numerical simulations show that local predation also leads to spontaneous pattern formation and to qualitative changes in the global dynamics of the system. In particular, depending on the size of the predation neighborhoods, the chaotic strange attractor present in the original model of Hastings and Powell can be replaced by a stable fixed point or by an attractor of simpler topology. (c) 2005 Elsevier B.V. All rights reserved.191229130

Random initial condition in small Barabasi-Albert networks and deviations from the scale-free behavior

Barabasi-Albert networks are constructed by adding nodes via preferential attachment to an initial core of nodes. We study the topology of small scale-free networks as a function of the size and average connectivity of their initial random core. We show that these two parameters may strongly affect the tail of the degree distribution, by consistently leading to broad-scale or single-scale networks. In particular, we argue that the size of the initial network core and its density of connections may be the main responsible for the exponential truncation of the power-law behavior observed in some small scale-free networks.713