Quick and label-free detection for Coumaphos by using surface plasmon resonance biochip

Simple and Fast Pesticide Nanosensors: Example of Surface Plasmon Resonance Coumaphos Nanosensor

Here, a molecular imprinting technique was employed to create an SPR-based nanosensor for the selective and sensitive detection of organophosphate-based coumaphos, a toxic insecticide/veterinary drug often used. To achieve this, UV polymerization was used to create polymeric nanofilms using N-methacryloyl-l-cysteine methyl ester, ethylene glycol dimethacrylate, and 2-hydroxyethyl methacrylate, which are functional monomers, cross-linkers, and hydrophilicity enabling agents, respectively. Several methods, including scanning electron microscopy (SEM), atomic force microscopy (AFM), and contact angle (CA) analyses, were used to characterize the nanofilms. Using coumaphos-imprinted SPR (CIP-SPR) and non-imprinted SPR (NIP-SPR) nanosensor chips, the kinetic evaluations of coumaphos sensing were investigated. The created CIP-SPR nanosensor demonstrated high selectivity to the coumaphos molecule compared to similar competitor molecules, including diazinon, pirimiphos-methyl, pyridaphenthion, phosalone, N-2,4(dimethylphenyl) formamide, 2,4-dimethylaniline, dimethoate, and phosmet. Additionally, there is a magnificent linear relationship for the concentration range of 0.1-250 ppb, with a low limit of detection (LOD) and limit of quantification (LOQ) of 0.001 and 0.003 ppb, respectively, and a high imprinting factor (I.F.4.4) for coumaphos. The Langmuir adsorption model is the best appropriate thermodynamic approach for the nanosensor. Intraday trials were performed three times with five repetitions to statistically evaluate the CIP-SPR nanosensor's reusability. Reusability investigations for the two weeks of interday analyses also indicated the three-dimensional stability of the CIP-SPR nanosensor. The remarkable reusability and reproducibility of the procedure are indicated by an RSD% result of less than 1.5. Therefore, it has been determined that the generated CIP-SPR nanosensors are highly selective, rapidly responsive, simple to use, reusable, and sensitive for coumaphos detection in an aqueous solution. An amino acid, which was used to detect coumaphos, included a CIP-SPR nanosensor manufactured without complicated coupling methods and labelling processes. Liquid chromatography with tandem mass spectrometry (LC/MS-MS) studies was performed for the validation studies of the SPR.

A Versatile One-Step Competitive Fiber Optic Surface Plasmon Resonance Bioassay Enabled by DNA Nanotechnology

Fiber optic surface plasmon resonance (FO-SPR)-based biosensors have emerged as powerful tools for biomarker detection due to their ability for real-time analysis of biomolecular interactions, cost-effectiveness, and user-friendliness. However, as (FO-)SPR signals are determined by the mass of the target molecules, the detection of low-molecular-weight targets remains challenging and currently requires tedious labeling and preparation steps. Therefore, in this work, we established a new concept for low-molecular-weight target detection by implementing duplexed aptamers on an FO-SPR sensor. In this manner, we enabled one-step competitive detection and could achieve significant signals, independent of the weight of the target molecules, without requiring labeling or preprocessing steps. This was demonstrated for the detection of a small molecule (ATP), protein (thrombin), and ssDNA target, thereby reaching detection limits of 72 μM, 36 nM, and 30 nM respectively and proving the generalizability of the proposed bioassay. Furthermore, target detection was successfully achieved in 10-fold diluted plasma, which demonstrated the applicability of the assay in biologically relevant matrices. Altogether, the developed one-step competitive FO-SPR bioassay opens up possibilities for the detection of low-molecular-weight targets in a fast and straightforward manner.

Speckle Noise Removal in Image-based Detection of Refractive Index Changes in Porous Silicon Microarrays

Based on porous silicon (PSi) microarray images, we propose a new method called the phagocytosis algorithm (PGY) for removing the influence of speckle noise on image gray values. In a theoretical analysis, speckle noise of different intensities is added to images, and a suitable denoising method is developed to restore the image gray level. This method can be used to reduce the influence of speckle noise on the gray values of PSi microarray images to improve the accuracy of detection and increase detection sensitivity. In experiments, the method is applied to detect refractive index changes in PSi microcavity images, and a good linear relationship between the gray level change and the refractive index change is obtained. In addition, the algorithm is applied to a PSi microarray image, and good results are obtained.

Image Processing of Porous Silicon Microarray in Refractive Index Change Detection

A new method for extracting the dots is proposed by the reflected light image of porous silicon (PSi) microarray utilization in this paper. The method consists of three parts: pretreatment, tilt correction and spot segmentation. First, based on the characteristics of different components in HSV (Hue, Saturation, Value) space, a special pretreatment is proposed for the reflected light image to obtain the contour edges of the array cells in the image. Second, through the geometric relationship of the target object between the initial external rectangle and the minimum bounding rectangle (MBR), a new tilt correction algorithm based on the MBR is proposed to adjust the image. Third, based on the specific requirements of the reflected light image segmentation, the array cells are segmented into dots as large as possible and the distance between the dots is equal in the corrected image. Experimental results show that the pretreatment part of this method can effectively avoid the influence of complex background and complete the binarization processing of the image. The tilt correction algorithm has a shorter computation time, which makes it highly suitable for tilt correction of reflected light images. The segmentation algorithm makes the dots in a regular arrangement, excludes the edges and the bright spots. This method could be utilized in the fast, accurate and automatic dots extraction of the PSi microarray reflected light image.

Parallel Detection of Refractive Index Changes in a Porous Silicon Microarray Based on Digital Images

A new technique for the refractive index change with high-sensitivity measurements was proposed by the digital image of porous silicon (PSi) microarray utilization in this paper. Under the irradiation of a He-Ne laser, the surface images of the PSi array cells with the microcavity structure were obtained by the digital imaging equipment, whereas the refractive index change of each array cells was detected by calculating the average gray value of the image and the refractive index change measurement sensitivity was 10^-4. This technique could be utilized in the label-free and parallel detection of refraction index changes induced by a biological reaction in the microarray or the chip.

Biosensor technology for pesticides--a review

Pesticides, due to their lucrative outcomes, are majorly implicated in agricultural fields for crop production enhancement. Due to their pest removal properties, pesticides of various classes have been designed to persist in the environment over a longer duration after their application to achieve maximum effectiveness. Apart from their recalcitrant structure and agricultural benefits, pesticides also impose acute toxicological effects onto the other various life forms. Their accumulation in the living system may prove to be detrimental if established in higher concentrations. Thus, their prompt and accurate analysis is a crucial matter of concern. Conventional techniques like chromatographic techniques (HPLC, GC, etc.) used for pesticides detection are associated with various limitations like stumpy sensitivity and efficiency, time consumption, laboriousity, requirement of expensive equipments and highly trained technicians, and many more. So there is a need to recruit the methods which can detect these neurotoxic compounds sensitively, selectively, rapidly, and easily in the field. Present work is a brief review of the pesticide effects, their current usage scenario, permissible limits in various food stuffs and 21st century advancements of biosensor technology for pesticide detection. Due to their exceptional performance capabilities, easiness in operation and on-site working, numerous biosensors have been developed for bio-monitoring of various environmental samples for pesticide evaluation immensely throughout the globe. Till date, based on sensing element (enzyme based, antibody based, etc.) and type of detection method used (Electrochemical, optical, and piezoelectric, etc.), a number of biosensors have been developed for pesticide detection. In present communication, authors have summarized 21st century's approaches of biosensor technology for pesticide detection such as enzyme-based biosensors, immunosensors, aptamers, molecularly imprinted polymers, and biochips technology. Also, the major technological advancements of nanotechnology in the field of biosensor technology are discussed. Various biosensors mentioned in manuscript are found to exhibit storage stability of biocomponent ranging from 30-60 days, detection limit of 10(-6) - 10(-16) M, response time of 1-20 min and applications of developed biosensors in environmental samples (water, food, vegetables, milk, and juice samples, etc.) are also discussed. Researchers all over the globe are working towards the development of different biosensing techniques based on contrast approaches for the detection of pesticides in various environmental samples.