Aggregation-based colorimetric sensor for determination of prothioconazole fungicide using colloidal silver nanoparticles (AgNPs)

Development of a colorimetric sensor array based on monometallic and bimetallic nanoparticles for discrimination of triazole fungicides

Due to the widespread use of pesticides and their harmful effects on humans and wildlife, monitoring their residual amounts in crops is critically essential but still challenging regarding the development of high-throughput approaches. Herein, a colorimetric sensor array has been proposed for discrimination and identification of triazole fungicides using monometallic and bimetallic silver and gold nanoparticles. Aggregation-induced behavior of AgNPs, AuNPs, and Au-AgNPs in the presence of four triazole fungicides produced a fingerprint response pattern for each analyte. Innovative changes to the metal composition of nanoparticles leads to the production of entirely distinct response patterns that can be used for the detection and discrimination of triazoles. Pattern recognition methods, including linear discriminant analysis (LDA) and hierarchical cluster analysis, have been employed for the differentiation of triazoles in the concentration range of 0.1-0.55 μg mL^-1. Besides, the sensor array demonstrates promising practicability to satisfactorily distinguished triazole in mixtures and complex media of wheat flour and cucumber samples. The proposed colorimetric sensor array might pave the way towards a cost-effective and rapid, yet sensitive platform for high-throughput monitoring of residual amounts of pesticides for on-site applications.

Silver Nanoparticles as Colorimetric Sensors for Water Pollutants

This review provides an up-to-date overview on silver nanoparticles-based materials suitable as optical sensors for water pollutants. The topic is really hot considering the implications for human health and environment due to water pollutants. In fact, the pollutants present in the water disturb the spontaneity of life-related mechanisms, such as the synthesis of cellular constituents and the transport of nutrients into cells, and this causes long / short-term diseases. For this reason, research continuously tends to develop always innovative, selective and efficient processes / technologies to remove pollutants from water. In this paper we will report on the silver nanoparticles synthesis, paying attention to the stabilizers and mostly used ligands, to the characterizations, to the properties and applications as colorimetric sensors for water pollutants. As water pollutants our attention will be focused on several heavy metals ions, such as Hg(II), Ni(II),Cu(II), Fe(III), Mn(II), Cr(III/V) Co(II) Cd(II), Pb(II), due to their dangerous effects on human health. In addition, several systems based on silver nanoparticles employed as pesticides colorimetric sensors in water will be also discussed. All of this with the aim to provide to readers a guide about recent advanced silver nanomaterials, used as colorimetric sensors in water.

ThThnated Development of a pH assisted AgNP-based colorimetric sensor Array for simultaneous identification of phosalone and azinphosmethyl pesticides

Development of simple and rapid methods for identification of pesticides, due to their broad usage and harmful effects on mammals, has been known as a critical demand. Herein, we have introduced a silver nanoparticle (AgNP) based colorimetric sensor array for simultaneous identification of Azinphosmethyl (AM) and Phosalone (PS) pesticides. In the presence of the target pesticides, unmodified AgNPs at various pHs (4.5, 5.5 and 9.5) showed different aggregation behaviors. As a result of aggregation, the color and UV-Vis spectra of AgNPs changed differentially, leading to distinct response patterns for AM and PS. The aggregation induced spectral changes of AgNPs, were used to identify AM and PS with the help of linear discriminant analysis (LDA). The applicability of the proposed sensor array was then evaluated by identifying the target pesticides in apple samples. Altogether, the developed AgNPs based colorimetric sensor array can be potentially exploited as an efficient discrimination tool in the near future for agrichemical applications.

Chemiluminometric fingerprints for identification of plasmonic nanoparticles

Development of a convenient and inexpensive method for identification and detection of nanoparticles (NPs) is of great interest. In this work, we have developed a novel and simple chemiluminescence based sensor array, with its sensing mechanism mimicking that of olfactory and gustatory systems for discriminating a set of NPs. The proposed method is based on the enhancement effect of NPs on luminol-oxidant CL intensity by their catalytic effect. Three kinds of oxidant including H₂O₂, AgNO₃, and K₃Fe(CN)₆ were used as sensor elements and NPs exhibited diverse enhancing responses to different oxidant-luminol CL systems producing unique response patterns that were identified through heat map and chemometric methods, including linear discriminant analysis (LDA) and hierarchical cluster analysis (HCA). Five NPs have been well distinguished at various concentrations. In addition, this method clearly revealed a linear relationship between CL signal values and the concentrations of NPs for the quantitative detection of NPs. We believe that this type of CL sensor array can open a new way for facile discrimination and detection of different kinds of NPs.

Aptamer immobilization on amino-functionalized metal-organic frameworks: an ultrasensitive platform for the electrochemical diagnostic of Escherichia coli O157:H7

Herein, we report the development of an electrochemical biosensor for Escherichia coli O157:H7 diagnostic based on amino-functionalized metal-organic frameworks (MOFs) as a new generation of organic-inorganic hybrid nanocomposites. The electrical and morphological properties of MOFs were enhanced by interweaving each isolated MOF crystal with polyaniline (PANI). Subsequent attachment of the amine-modified aptamer to the polyanilinated MOFs was accomplished using glutaraldehyde (GA) as a cross-linking agent. The prepared biocompatible platform was carefully characterized by means of field-emission scanning electron microscopy (FESEM), energy-dispersive spectroscopy (EDS), Fourier transform infrared spectroscopy (FT-IR), and X-ray powder diffraction (XRD) techniques. The biosensor fabrication and its electrochemical characterizations were monitored by cyclic voltammetry (CV) and electrochemical impedance spectroscopy (EIS) techniques. Differential pulse voltammetry (DPV) was applied to monitoring and quantitation of the interaction between the aptamer and E. coli O157:H7 using methylene blue (MB) as an electrochemical indicator. Changes in the reduction peak current of MB in the presence of E. coli O157:H7 was recorded as an analytical signal and indicated a relationship with the logarithm of the E. coli O157:H7 concentration in the range of 2.1 × 10¹ to 2.1 × 10⁷ CFU mL^-1 with a LOQ of 21 CFU mL^-1 and LOD of 2 CFU mL^-1. The electrochemical aptasensor displayed good recovery values for the detection of E. coli O157:H7 in environmental real samples and also could act as a smart device to investigate the effects of antibacterial agents against E. coli O157:H7.

Label-free detection of β-amyloid peptides (Aβ40 and Aβ42): a colorimetric sensor array for plasma monitoring of Alzheimer's disease

Monitoring the ratio of 40- and 42-residue amyloid β peptides (i.e., Aβ40 and Aβ42) in human plasma is considered one of the hallmarks of detection of the early stage of Alzheimer's disease (AD). Therefore, development of a specific, yet non-antibody-based method for simultaneous detection of Aβ40 and Aβ42 may have considerable clinical applications. Here, we developed a 'nanoparticle-based colorimetric sensor array' utilizing label-free gold and silver nanoparticles for visual detection of Aβ42 and Aβ40. Different aggregation behaviors of nanoparticles through their conjugation with Aβ42 and Aβ40 followed by the coordination of Aβ42 and Aβ40 with Cu(ii) led to diverse spectral and color changes. The spectral changes were quantitatively differentiated by a supervised pattern recognition approach, linear discriminant analysis (LDA). The proposed sensor array was able to discriminate among Aβ42, Aβ40, and HSA in different concentrations (50 nmol L-1 to 500 nmol L-1) and their mixtures. Moreover, the sensor array had the capability to identify structurally similar Aβ peptides in human plasma samples. The developed sensor array technology might pave the way for a cheap and rapid, yet robust, platform for high-throughput screening of human plasma for defining the at-risk population for AD.