The enzyme requires O2 to oxidize the ethanol and the products formed are acetaldehyde and hydrogen peroxide. Since, AOX enzymatically converts all primary alcohols and formaldehyde [12], it suffers from a lack of selectivity to ethanol. However, this should not be a problem in the use of such a biosensor for analysis of ethanol in fermented beverage samples, since ethanol is present at much higher levels. The main problem of AOX-based biosensors is their limited stability. For this reason, several ways of stabilizing AOX in the dry state using a combination of polyelectrolytes and sugar derivatives have been studied [13,14].In this work the development of a novel and simple visual ethanol biosensor based on AOX immobilized onto a polyaniline (PANI) film is reported.

PANI is a polymer that changes conductivity and colour with changes in pH or redox reactions as a result of changes in the degree of protonation of the polymer backbone, making it useful as an optical or a visual sensor. PANI film itself acts both as a matrix support compatible with biomaterial (e.g., enzyme) and as the indicator, and can be easily be fabricated [15,16]. Furthermore, PANI has already been reported as a polymeric matrix in chemical sensors [17�C19] and biosensors [20�C24] developments. In the case of a PANI-based biosensor, most employ a class of enzymes known as oxido-reductases, mainly oxidases and dehydrogenases. In the case of oxidases, they are mainly based on peroxidase, glucose oxidase, or cholesterol oxidase [25]. A few of them used lipase [26], invertase [27] and polyphenol oxidase [28], and very few of them have used AOX.

Here, we used AOX as enzyme catalyst for ethanol detection, coupled with the optical properties of PANI as a visual sensor, so that it the presence of the alcohol could be detected by the naked eye due to a colour change from green to blue. For quantitative detection, the colour change of the films towards ethanol has been scanned and analysed using image analysis software (i.e., ImageJ). Optimisation of experimental conditions has been carried out and the analytical parameters of the biosensor have been determined. The operational and storage stability of the biosensor were also evaluated.2.?Experimental2.1. Reagents and SolutionsAniline (AR-grade), alcohol oxidase (AOX) (A2404, EC1.1.3.

13, 10�C40 units/mg protein, from Pichia pastoris), ascorbic acid (A5960), gallic acid (G7384) and Anacetrapib l-cysteine (W326305) were purchased from Sigma-Aldrich (Saint Louis, MO, USA). Absolute ethanol (>99.5%), methanol, orthophosphoric acid 85% and sodium hydroxide (pellets) were delivered by Merck (Nottingham, UK). All chemicals were of analytical reagent grade. The Milli-Q water used was obtained from a Millipore Direct-QTM 5 purification system. Stock solutions of ethanol was prepared daily in 0.

In this study, GeoWEPP (WEPP v2006.5) was used to estimate the sediment yield and runoff in Orcan Creek watershed of Kahramanmaras. 1|]# The sediment yield and runoff results from the GeoWEPP model were compared with the observed monthly data collected from the sample watershed to evaluate the performance of the model.2.?Material and Method2.1. GeoWEPPGeoWEPP was developed as a collaborative project conducted by the Agriculture Research Service, Purdue University, and the USDA National Soil Erosion Research Laboratory [17]. To predict sediment yield and runoff at watershed scale, GeoWEPP integrates WEPP model and TOPAZ (TOpography PArameteriZation) software within the ArcView 3.2 (ArcView 2000) [17] (Figure 1).

In GeoWEPP, necessary input files (land cover, land use, slope, climate, soil, and management) are generated within WEPP and topographic data are parameterized by using TOPAZ based on DEMs [18]. Finally, watershed outputs are produced by using GIS functions in ArcView [7].Figure 1.Logic flowchart of the GeoWEPP.2.1.1. TOPAZIn GeoWEPP, hillslope profiles are generated by utilizing TOPAZ, which parameterizes topographic data based on DEMs. TOPAZ determines the channel network based on the steepest down slope path, considering 8 adjacent cells of each raster cell (pixel) [19]. The channel network can be adjusted by changing values of Mean Source Channel Length (MSCL) and Critical Source Area (CSA). The MSCL defines the shortest channel length and the CSA is the minimum drainage area [7, 19].

After defining the channel network, TOPAZ generates the sub-watersheds which represent the watershed (Figure 2).

Figure 2.The flow accumulation for sub-watersheds by using TOPAZ.2.1.2. ArcViewThe GeoWEPP model has a feature of being run in ArcView. The watershed outputs are generated as grid layers representing soil loss as a percentage of the tolerable soil loss (TSL). In the grid layers, areas that generate soil loss values greater than or less than the GSK-3 TSL are highlighted. The runoff and sediment yield data AV-951 for each pixel can be produced in text files or in grid outputs. Text files indicate average annual rainfall and number of storms, total runoff, soil loss, and sediment yield for each sub-watersheds and for the entire watershed [7].

2.1.3. WEPP Input FilesWEPP model requires four input files including slope, climate, soil, and management files to describe hillslope geometry, meteorological characteristics, soil properties, and ground cover, respectively.Slope FileThe slope file is generated based on necessary hillslope parameters such as slope gradient, shape, width, and orientation along its length. GeoWEPP utilizes TOPAZ to produce sub-watershed profiles based on DEM data (Figure 3).

(Steps 1, 2) stepwise deposition of poly electrolyte layers; (Step 3) Exposure of the enzyme to solutions of pH > …Yu et al. employed a similar approach to encapsulate CAT into polyelectrolytes, PAH and PSS respectively [14]. They investigated the direct electron transfer behavior and electrocatalytic response of polyelectrolyte encapsulated CAT to H2O2 reduction. The polyelectrolyte encapsulated CAT displays 4.5 times higher electrocatalytic response to H2O2 than non-encapsulated and solubilized CAT. However, the relative increase in catalytic response at the former was not proportional to the amount of enzyme deposited, since the entire CAT molecules were not found in their electrocatalytic active site.

This might be due to the reason that the distance between the CAT molecules and the electrode surface gets significantly increased after polyelectrolyte encapsulation. Furthermore, they observed through their detailed studies that, with increases in precursor polyelectrolyte layer number, the current response to H2O2 decreased significantly, while the electrode response time increased. In contrast, implementation of fewer polyelectrolyte layers lead to sensitive and fast response in H2O2 determinations. This approach of encapsulating CAT micro crystals into polyelectrolyte layers for biosensing provides a versatile approach to prepare high enzyme content films with improved enzyme activities.2.2. Surfactant Modified Matrices for CAT ImmobilizationIn an alternative approach, Chen et al. attempted to immobilize CAT onto cationic surfactant, (didodecyldimethylammonium bromide, DDAB) liquid crystal films [15].

They revealed through their results that the electron transfer of CAT is greatly improved in the AV-951 presence of DDAB. The electron transfer rate constant (ks) was observed to be 3.0 �� 0.4 s?1. However, their circular dichroism (CD) results illustrated that the conformation of CAT gets slightly perturbed by the hydrophobic nature of DDAB (Figure 2). The CD spectrum of CAT exhibits a negative peak at 237 nm, whereas for CAT-DDAB film it was observed at 232 nm. The negative peak at 232 nm was regarded as the shift from 237 nm of CAT film alone.Figure 2.CD spectra of CAT (�� ��), DDAB (�C �C �C), CAT-DDAB (��) films. CAT was prepared in pH 6.1, 10 mM phosphate buffer solution (PBS) with 50 mmol: l KCl. Temperature: 25��C (reproduced with permission from …Gebica et al. also studied the interaction of th
As the planet��s exploding human population results in massive developments and changes to the landscape, there is a consequent need for efficient and cost-effective methods to locate, map, and acquire information from sites of our cultural heritage before they are forever lost [1].