Use of response surface methodology in a fed-batch process for optimization of tricarboxylic acid cycle intermediates to achieve high levels of canthaxanthin from Dietzianatronolimnaea HS-1

In this work, we applied statistical experimental design to a fed-batch process for optimization of tricarboxylic acid cycle (TCA) intermediates in order to achieve high-level production of canthaxanthin from Dietzia natronolimnaea HS-1 cultured in beet molasses. A fractional factorial design (screening test) was first conducted on five TCA cycle intermediates. Out of the five TCA cycle intermediates investigated via screening tests, alfaketoglutarate, oxaloacetate and succinate were selected based on their statistically significant (P < 0.05) and positive effects on canthaxanthin production. These significant factors were optimized by means of response surface methodology (RSM) in order to achieve high-level production of canthaxanthin. The experimental results of the RSM were fitted with a second-order polynomial equation by means of a multiple regression technique to identify the relationship between canthaxanthin production and the three TCA cycle intermediates. By means of this statistical design under a fed-batch process, the optimum conditions required to achieve the highest level of canthaxanthin (13172 ± 25 μg l⁻¹) were determined as follows: alfaketoglutarate, 9.69 mM; oxaloacetate, 8.68 mM; succinate, 8.51 mM.     

On the use of the FluoroProbe®, a phytoplankton quantification method based on fluorescence excitation spectra for large-scale surveys of lakes and reservoirs

Although microscope analysis is very useful for studying phytoplankton community composition, it does not allow for high frequency (spatial and/or temporal) data acquisition. In an attempt to overcome this issue, fluorescence-based approaches that use selective excitation of pigment antennae have spread rapidly. However, the ability of spectral fluorescence to provide accurate estimates of phytoplankton biomass and composition is still debated, and only a few datasets have been tested to date.In this study, we sampled of a wide range of water bodies (n = 50) in the Ile-de-France region (North Central France). We used the resulting extensive dataset to assess the ability of the bbe-Moldaenke FluoroProbe II (FP) to estimate phytoplankton community composition in lakes and reservoirs.We demonstrated that FP data yields better estimates of total phytoplankton biovolume than do spectrophotometric chlorophyll a measures and that FP data can be further corrected using the average chlorophyll a to biovolume ratio among phytoplankton groups. Overall, group-specific relationships between FP and biovolume data were consistent. However, we identified a number of cases where caution is required. We found that Euglenophytes are expected to depart from the global FP vs. biovolume relationship of the ‘green’ group due to varying Fv/Fm and pigment content in response to environmental conditions (photoautotrophic vs. photoheterotrophic growth). Then, it appears necessary to consider the composition of the Chromophytes community in order to obtain a good agreement between both biomass estimation methods. Finally, we confirmed the misattribution toward the ‘red’ group of phycoerythrin-containing cyanobacteria and the occurrence of a strong scattering in the relationship between the FP vs. biovolume of the ‘blue’ group that can be partly attributed to the occurrence of large colony-forming cyanobacteria (e.g., Microcystis spp, Aphanizomenon flos-aquae).We propose correcting procedures to improve the quality of data obtained from spectral fluorescence tools in the context of large-scale sampling of lakes and reservoirs.     

Prosopis farcta Seeds: Potential Source of Protein and Unsaturated Fatty Acids?

The goal of this study is to evaluate the chemical composition of the Prosopis farcta seeds. The Kjeldahl method revealed that the level of the total protein was ca. 18 % on a dry weight basis (DW). Gas chromatographic analysis revealed the presence of six fatty acids. Linoleic acid with 57.55 % was the major fatty acid, followed by oleic and palmitic acids (24.58 and 12.91 %, respectively). Total phenolic content was 1.71 mg GAE/g DW (GAE = gallic acid equivalents). Methanolic extracts showed important antioxidant properties. This work highlights the importance of P. farcta seeds as natural and inexpensive sources of protein, unsaturated fatty acid, and phenolic compounds for both cosmetic and pharmaceutical uses.     

β-Cyclodextrin Encapsulation of Synthetic AHLs: Drug Delivery Implications and Quorum-Quenching Exploits

Many bacteria, such as Pseudomonas aeruginosa, regulate phenotypic switching in a population density-dependent manner through a phenomenon known as quorum sensing (QS). For Gram-negative bacteria, QS relies on the synthesis, transmission, and perception of low-molecular-weight signal molecules that are predominantly N-acyl-l -homoserine lactones (AHLs). Efforts to disrupt AHL-mediated QS have largely focused on the development of synthetic AHL analogues (SAHLAs) that are structurally similar to native AHLs. However, like AHLs, these molecules tend to be hydrophobic and are poorly soluble under aqueous conditions. Water-soluble macrocycles, such as cyclodextrins (CDs), that encapsulate hydrophobic guests have long been used by both the agricultural and pharmaceutical industries to overcome the solubility issues associated with hydrophobic compounds of interest. Conveniently, CDs have also demonstrated anti-AHL-mediated QS effects. Here, using fluorescence spectroscopy, NMR spectrometry, and mass spectrometry, we evaluate the affinity of SAHLAs, as well as their hydrolysis products, for β-CD inclusion. We also evaluated the ability of these complexes to inhibit wild-type P. aeruginosa virulence in a Caenorhabditis elegans host infection study, for the first time. Our efforts confirm the potential of β-CDs for the improved delivery of SAHLAs at the host/microbial interface, expanding the utility of this approach as a strategy for probing and controlling QS.     

Fabrication of g-C3N4/Au nanocomposite using laser ablation and its application as an effective catalyst in the reduction of organic pollutants in water

Gold nanoparticles (Au NPs) were fabricated by laser ablation in liquid (LAL) as a green method and decorated on graphitic carbon nitride (g-C₃N₄) by a facile ultrasonication method. g-C₃N₄ was prepared via urea pyrolysis. The prepared g-C₃N₄/Au (denoted as CN/Au) nanocomposite was characterized using X-ray diffraction (XRD), Fourier transform infrared (FTIR), X-ray photoelectron spectroscopy (XPS), transmission electron microscopy (TEM), field emission scanning electron microscopy (FESEM) and energy dispersive X-ray spectrometry (EDS). The synthesized CN/Au nanocomposite was applied as an efficient catalyst in the reduction of 4-nitrophenol (4-NP) and methyl orange (MO) using NaBH₄ at room temperature. The recyclability of CN/Au catalyst was examined.     

Fuzzy-Q-learning-based autonomic management of macro-diversity algorithm in UMTS networks

Third generationUmts network has come with significant high-quality services that considerably increase the complexity of its management. Autonomic management has been introduced to alleviate these complex lengthy tasks. In this paper, we propose an autonomic management of macro-diversity algorithm inUmts networks. The new approach allows to dynamically adapt macro-diversity parameters to varying network situations. The online adaptation of these parameters is made by an intelligent controller calledfuzzy-Q-Learning. The combination of Fuzzy Inference System (Fis) and Q-learning algorithm allows to determine the best on-line parameterization of base stations and to deal with large number of continuous states and actions. The proposed scheme improves the system capacity up to 30% compared to a classical network with fixed parameters, balances the load between base stations and minimizes human interventions in the network management. However, the reactivity of the controller should be chosen with a special care since it impacts the frequency of active set updates and hence signalling messages in the radio interface as well as in the core network.     

Adaptive image compression technique for wireless sensor networks

When using wireless sensor networks for real-time image transmission, some critical points should be considered. These points are limited computational power, storage capability, narrow bandwidth and required energy. Therefore, efficient compression and transmission of images in wireless sensor network is considered. To address the above mentioned concerns, an efficient adaptive compression scheme that ensures a significant computational and energy reduction as well as communication with minimal degradation of the image quality is proposed. This scheme is based on wavelet image transform and distributed image compression by sharing the processing of tasks to extend the overall lifetime of the network. Simulation results are presented and they show that the proposed scheme optimizes the network lifetime, reduces significantly the amount of the required memory and minimizes the computation energy by reducing the number of arithmetic operations and memory accesses.