Impact of Microalgae-Bacteria Interactions on the Production of Algal Biomass and Associated Compounds.

A greater insight on the control of the interactions between microalgae and other microorganisms, particularly bacteria, should be useful for enhancing the efficiency of microalgal biomass production and associated valuable compounds. Little attention has been paid to the controlled utilization of microalgae-bacteria consortia. However, the studies of microalgal-bacterial interactions have revealed a significant impact of the mutualistic or parasitic relationships on algal growth. The algal growth, for instance, has been shown to be enhanced by growth promoting factors produced by bacteria, such as indole-3-acetic acid. Vitamin B12 produced by bacteria in algal cultures and bacterial siderophores are also known to be involved in promoting faster microalgal growth. More interestingly, enhancement in the intracellular levels of carbohydrates, lipids and pigments of microalgae coupled with algal growth stimulation has also been reported. In this sense, massive algal production might occur in the presence of bacteria, and microalgae-bacteria interactions can be beneficial to the massive production of microalgae and algal products. This manuscript reviews the recent knowledge on the impact of the microalgae-bacteria interactions on the production of microalgae and accumulation of valuable compounds, with an emphasis on algal species having application in aquaculture.

IDENTIFICATION AND PHYSIOLOGICAL ASPECTS OF A NOVEL CAROTENOID-ENRICHED, METAL-RESISTANT MICROALGA ISOLATED FROM AN ACIDIC RIVER IN HUELVA (SPAIN)(1).

A heavy-metal-resistant, carotenoid-enriched novel unicellular microalga was isolated from an acidic river in Huelva, Spain. The isolated ribosomal 18S subunit rDNA sequence showed homology with known sequences from green microalgae, the closest sequence (98% homology) belonging to the genus Coccomyxa. The isolated microalga therefore was an up to now uncultured microalga. The microalga was isolated from Tinto River area (Huelva, Spain), an acidic river that exhibits very low pH (1.7-3.1) with high concentrations of sulfuric acid and heavy metals, including Fe, Cu, Mn, Ni, and Al. Electron micrographs show that the microalga contains a large chloroplast with a presence of lipid droplets, an increased number of starch bodies as well as electron-dense deposits and plastoglobules, the last observed only in iron-exposed cells. Unlike other acidophile microalgae, the isolated microalga showed high growth rates when cultivated photoautotrophycally (up to 0.6 d(-1) ) in a suitable culture medium prepared at our laboratory. The growth was shown to be iron dependent. When the microalga is grown in fluidized bed reactors, the high growth rates resulted in unexpectedly high productivities for being a microalga that naturally grows in acidic environments (0.32 g·L(-1) ·d(-1) ). The microalga also grows optimally on reduced carbon sources, including glucose and urea, and at an optimal temperature of 35°C. The alga pigment profile is particularly rich in carotenoids, especially lutein, suggesting that the microalga might have potential for antioxidant production, namely, xanthophylls.

Impedimetric detection of double-tagged PCR products using novel amplification procedures based on gold nanoparticles and Protein G.

Double-tagged DNA coming from PCR amplification of a Salmonella spp. sample was detected by an electrochemical impedimetric genosensor based on avidin bulk-modified graphite-epoxy biocomposite (Av-GEB). The double-tagging PCR strategy provided the amplicon with both biotin and digoxigenin (DIG) moieties. The immobilization of the double-tagged DNA was based on its biotin moiety, while the DIG label was used for signal amplification. Impedance spectra were recorded to detect the change in interfacial charge transfer resistance (R(ct)), experimented by the redox marker ferri-/ferro-cyanide after the avidin-biotin fixation of the sample DNA onto the electrode surface. A further step in the genosensing strategy was the amplification of impedimetric signal by the use of an enhancing procedure. The latter was based on the reaction of the DIG moiety belonging to the amplicon with an anti-DIG antibody from mouse. Two different secondary enhancing steps based both on gold nanoparticle-labelled anti-mouse IgG or on Protein G were performed and compared for improving assay sensitivity.

Wavelet neural networks to resolve the overlapping signal in the voltammetric determination of phenolic compounds.

Three phenolic compounds, i.e. phenol, catechol and 4-acetamidophenol, were simultaneously determined by voltammetric detection of its oxidation reaction at the surface of an epoxy-graphite transducer. Because of strong signal overlapping, Wavelet Neural Networks (WNN) were used in data treatment, in a combination of chemometrics and electrochemical sensors, already known as the electronic tongue concept. To facilitate calibration, a set of samples (concentration of each phenol ranging from 0.25 to 2.5mM) was prepared automatically by employing a Sequential Injection System. Phenolic compounds could be resolved with good prediction ability, showing correlation coefficients greater than 0.929 when the obtained values were compared with those expected for a set of samples not employed for training.

Nutrient solution monitoring in greenhouse cultivation employing a potentiometric electronic tongue.

This work investigates the use of electronic tongues for monitoring nutrient solution compositions in closed soilless systems. This is a horticultural technique in which the nutrient solution is continuously recirculated and an automatic recomposition system maintains the concentration of the different ions in the optimum range for the plants. Electronic tongues used in this study comprised an array of potentiometric sensors and complex data processing by artificial neural networks. A first experiment was able to carry out the simultaneous inline monitoring of ammonium, potassium, sodium, chloride, and nitrate ions during the winter. In the second and third applications, done during summer, some changes were introduced in the sensor array to improve its response toward chloride ions and to incorporate phosphate in the model. This electronic tongue was validated with real greenhouse samples and was also able to detect the variations in the ion concentrations caused by an incorrect configuration of the recomposition system.

Automated electronic tongue based on potentiometric sensors for the determination of a trinary anionic surfactant mixture.

An automated electronic tongue consisting of an array of potentiometric sensors and an artificial neural network (ANN) has been developed to resolve mixtures of anionic surfactants. The sensor array was formed by five different flow-through sensors for anionic surfactants, based on poly(vinyl chloride) membranes having cross-sensitivity features. Feedforward multilayer neural networks were used to predict surfactant concentrations. As a great amount of information is required for the correct modelling of the sensors response, a sequential injection analysis (SIA) system was used to automatically provide it. Dodecylsulfate (DS(-)), dodecylbenzenesulfonate (DBS(-)) and alpha-alkene sulfonate (ALF(-)) formed the three-analyte study case resolved in this work. Their concentrations varied from 0.2 to 4mM for ALF(-) and DBS(-) and from 0.2 to 5mM for DS(-). Good prediction ability was obtained with correlation coefficients better than 0.933 when the obtained values were compared with those expected for a set of 16 external test samples not used for training.

Characterization of an ion-selective polypyrrole coating and application to the joint determination of potassium, sodium and ammonium by electrochemical impedance spectroscopy and partial least squares method.

A stable immobilization of ionophores (INPHs) was achieved by selectively electropolymerizing overoxidized pyrrol on the working electrode surface. The optimal conditions found allowed the immobilization of a huge amount of INPH which remained its recognition properties. A single sensing chip, containing a generic INPH or an INPH mixture, was employed to the joint quantification of potassium, ammonium and sodium in fertilizer samples. Electrochemical impedance spectroscopy (EIS) and partial least square (PLS) regression were used to obtain and process the data, respectively. The sensing element (INPH) and the exposure time were optimized. The best results were obtained by using the dibenzo-18-crown-6 INPH after waiting for 60s, the time required to stabilize the impedimetric measurement. Taking into account that a single chip was employed, acceptable relative errors were obtained in the determination of potassium and ammonium (17% and 9%, respectively) in real fertilizer samples, also containing sodium. Although sodium concentration could not be estimated with precision, it had to be introduced into the calibration set data in order to model its interference with the other two ions.

EIS multianalyte sensing with an automated SIA system-An electronic tongue employing the impedimetric signal.

In this work, the simultaneous quantification of three alkaline ions (potassium, sodium and ammonium) from a single impedance spectrum is presented. For this purpose, a generic ionophore - dibenzo-18-crown-6 - was used as a recognition element, entrapped into a polymeric matrix of polypyrrole generated by electropolymerization. Electrochemical impedance spectroscopy (EIS) and artificial neural networks (ANNs) were employed to obtain and process the data, respectively. In fact, EIS detected the ions exchanged between the medium and the sensing layer whereas ANNs, after an appropriated training process, could turn the impedance spectrum into concentrations values. A sequential injection analysis (SIA) system was employed for operation and to automatically generate the information required for the training of the ANN. Best results were obtained by using a backpropagation neural network made up by two hidden layers: the first one contained three neurons with the radbas transfer function and the second one ten neurons with the tansig transfer function. Three commercial fertilizers were tested employing the proposed methodology on account of the high complexity of their matrix. The experimental results were compared with reference methods.

Sequential injection system with higher dimensional electrochemical sensor signals Part 2. Potentiometric e-tongue for the determination of alkaline ions.

An intelligent, automatic system based on an array of non-specific-response chemical sensors was developed. As a great amount of information is required for its correct modelling, we propose a system generating it itself. The sequential injection analysis (SIA) technique was chosen as it enables the processes of training, calibration, validation and operation to be automated simply. Detection was carried out using an array of potentiometric sensors based on PVC membranes of different selectivity. The diluted standard solutions needed for system learning and response modelling are automatically prepared from more concentrated standards. The electrodes used were characterised with respect to one and two analytes, by means of high-dimensionality calibrations, and the response surface of each was represented; this characterisation enabled an interference study of great practical utility. The combined response was modelled by means of artificial neural networks (ANNs), and thus it was possible to obtain an automated electronic tongue based on SIA. In order to identify the ANN which provided the best model of the electrode responses, some of the network's parameters were optimised and its usefulness in determining NH(4)(+), K(+) and Na(+) ions in synthetic samples was then tested. Finally, it was used to determine these ions in commercial fertilisers, the obtained results being compared with reference methods.

Application of a potentiometric electronic tongue as a classification tool in food analysis.

This paper reports on the application of a potentiometric sensor array to the food analysis field, in order to distinguish simple tastes and to classify food samples. This array is formed by a set of non-specific all-solid-state potentiometric sensors and has been used in combination with principal component analysis (PCA) for the classification of food samples in batch and in flow injection mode. First attempt was to classify synthetic samples prepared with controlled variability. Once this ability is proven, satisfactory classification results are presented for commercial waters, orange-based drinks and tea samples. An interesting correlation is achieved between the natural juice content and its first calculated component, which allows for a very simple tool for screening purposes.

Ginecomastía correlación clínico-patológica / Gynaecomastia: clinico-pathologic correlation

Se denomina ginecomastía a la hipertrofia de la glándula mamaria masculina. Puede ser fisiológica, familiar, patológica o inducida por drogas, aunque en muchos casos su etiología es desconocida, la ginecomastía es usualmente unilateral y asintomática. Los mecanismos que se involucran son: incremento de la estimulación de estrógenos, disminución de los niveles de testosteronay disminución de la relación andrógrenos/estrógenos. El tratamiento puede ser dirigido a la causa subyacente cuando ésta es identificada. Se estudiaron 24 pacientes con diagnóstico de ginecomastía comprendidos entre las edades de 14 a 30 añnos a quienes se les efectuó mastectomía subcutánea con incisión periareolar. Hubo dos complicaciones que consistieron en hematoma e infeción del área quirúrgica y remanente de tejido mamario redundante. Los análisis de laboratorio no fueron concluyentes para determinar la etiología